Data-based daily water consumption calculation and analysis method and system

Abstract

The invention is suitable for the technical field of water resource application, and provides a data-based daily water consumption calculation and analysis method and system, and the method comprises the steps: obtaining the historical water supply data of a city, and obtaining the existing data of the city, and the existing data comprise the population number and a water supply system; predicting population growth according to existing data, obtaining a prediction result, judging whether the water supply system is optimized or not according to the prediction result, obtaining an optimization method, and selecting a specific optimization method according to the prediction result; acquiring historical weather information, predicting weather change data according to the weather information, predicting hydrological variables according to the weather change data, and optimizing a water supply scheduling mode according to the hydrological variables; according to the method, the water plant data is obtained, the water plant data comprises the water supply capacity and the water supply safety margin, the water supply capacity comprises the water taking capacity, the processing capacity and the water conveying capacity, operation management of the water supply plant is optimized according to the water supply capacity, and the problems that an existing city is unclear in overall planning of water distribution and water utilization and has no effective basis are solved.

Description

Technical Field

[0001] The present invention belongs to the technical field of water resource application, and in particular relates to a data-based daily water consumption calculation and analysis method and system. Background Art

[0002] With the acceleration of urbanization and the continuous growth of population, urban water supply systems are facing increasingly severe challenges. In recent years, the frequent occurrence of extreme weather, such as drought, high temperature, heavy rain and other climate changes have significantly increased the impact of water supply.

[0003] The existing water supply scheduling model is relatively fixed and difficult to dynamically adjust according to weather changes, hydrological variables and fluctuations in water demand, resulting in insufficient water supply during peak periods and energy waste during low periods. In addition, the pressure control method of the pipeline network is relatively extensive, resulting in insufficient water supply pressure in remote areas, and pipeline leakage is prone to occur in high-pressure areas, increasing water supply losses.

[0004] The existing technology has the problem that the existing cities have unclear and ineffective basis for the overall planning of water allocation and water use. Summary of the invention

[0005] The purpose of the embodiment of the present invention is to provide a data-based daily water consumption calculation and analysis method, aiming to solve the problem raised in the third part of the background technology.

[0006] The embodiment of the present invention is implemented as follows: a method for calculating and analyzing daily water consumption based on data, the method comprising: Obtaining historical water supply data of the city and obtaining current data of the city, wherein the current data includes population and water supply system; Predict population growth based on existing data, obtain prediction results, determine whether the water supply system is optimized based on the prediction results, obtain optimization methods, and select specific optimization methods based on the prediction results; Obtain historical weather information, predict weather change data based on the weather information, predict hydrological variables based on the weather change data, and optimize the water supply scheduling method based on the hydrological variables; Acquire water plant data, wherein the water plant data includes water supply capacity and water supply safety margin, wherein the water supply capacity includes water intake capacity, treatment capacity and water transmission capacity, and optimize the operation and management of the water supply plant according to the water supply capacity.

[0007] Preferably, the steps of predicting population growth according to existing data, obtaining prediction results, judging whether the water supply system is optimized according to the prediction results, obtaining an optimization method, and selecting a specific optimization method according to the prediction results specifically include: Obtain the current population data and predict population growth based on the linear regression model. The linear regression model P t+n =P t +r×n; Obtain prediction results, obtain optimization thresholds for the water supply system, compare the prediction results with the optimization thresholds, and obtain comparison results; Determine whether the water supply system is optimized based on the comparison results, and select the specific optimization method based on the prediction results.

[0008] Preferably, the steps of obtaining historical weather information, predicting weather change data according to the weather information, predicting hydrological variables according to the weather change data, and optimizing the water supply scheduling method according to the hydrological variables specifically include: Obtain historical weather information, and predict weather change data based on the weather information, wherein the weather change data includes temperature and precipitation; Predicting hydrological variables based on weather change data, wherein the hydrological variables include precipitation and evaporation; The water supply scheduling method is optimized according to the hydrological variables, and the water supply scheduling method includes unified scheduling water supply, zone scheduling water supply and time-sharing scheduling water supply, and an optimization method is obtained and selected according to the water supply scheduling method.

[0009] Preferably, the water plant data is obtained, the water plant data includes water supply capacity and water supply safety margin, the water supply capacity includes water intake capacity, treatment capacity and water delivery capacity, and the step of optimizing the operation and management of the water supply plant according to the water supply capacity specifically includes: Acquiring water plant data, wherein the water plant data includes water supply capacity and water supply safety margin; Water supply capacity includes water intake capacity, treatment capacity and water transmission capacity, and water supply safety margin is the additional water supply capacity; The operation and management of the water supply plant is optimized according to the water supply capacity, and the operation and management includes water supply scheduling, operation load management, water source allocation, pipe network pressure control, equipment maintenance and emergency plans.

[0010] Preferably, the optimization method includes a ring layout of the water supply network, remote control of pipeline valves, and dynamic adjustment of water supply.

[0011] Another object of an embodiment of the present invention is to provide a data-based daily water consumption calculation and analysis system, the system comprising: The basic information module obtains the historical water supply data of the city and the existing data of the city, wherein the existing data includes the population and the water supply system; The water supply optimization module predicts population growth based on existing data, obtains the prediction results, determines whether the water supply system is optimized based on the prediction results, obtains the optimization method, and selects the specific optimization method based on the prediction results; The water supply scheduling module obtains historical weather information, predicts weather change data based on the weather information, predicts hydrological variables based on the weather change data, and optimizes the water supply scheduling method based on the hydrological variables; The water supply operation module obtains water plant data, which includes water supply capacity and water supply safety margin. The water supply capacity includes water intake capacity, processing capacity and water transmission capacity, and optimizes the operation management of the water supply plant according to the water supply capacity.

[0012] Preferably, the water supply optimization module includes: The population prediction unit obtains the current population data and predicts the population growth according to the linear regression model. The linear regression model P t+n =P t +r×n; A comparison unit obtains the prediction result, obtains the optimization threshold of the water supply system, compares the prediction result with the optimization threshold, and obtains the comparison result; The water supply optimization unit determines whether the water supply system is optimized based on the comparison results and selects a specific optimization method based on the prediction results.

[0013] Preferably, the water supply scheduling module includes: A weather unit, which obtains historical weather information and predicts weather change data based on the weather information, wherein the weather change data includes temperature and precipitation; A hydrological variable unit, which predicts hydrological variables according to weather change data, wherein the hydrological variables include precipitation and evaporation; The water supply scheduling unit optimizes the water supply scheduling mode according to the hydrological variables, wherein the water supply scheduling mode includes unified scheduling water supply, zone scheduling water supply and time-sharing scheduling water supply, obtains the optimization method, and selects the optimization method according to the water supply scheduling mode.

[0014] Preferably, the water supply operation module includes: A water plant unit, which obtains water plant data, wherein the water plant data includes water supply capacity and water supply safety margin; Water supply capacity unit, water supply capacity includes water intake capacity, treatment capacity and water transmission capacity, and water supply safety margin is the additional water supply capacity; The water supply operation unit optimizes the operation management of the water supply plant according to the water supply capacity. The operation management includes water supply scheduling, operation load management, water source allocation, pipe network pressure control, equipment maintenance and emergency plans.

[0015] Preferably, the optimization method includes a ring layout of the water supply network, remote control of pipeline valves, and dynamic adjustment of water supply.

[0016] The embodiment of the present invention provides a data-based daily water consumption calculation and analysis method, which obtains historical water supply data of a city, obtains existing data of the city, obtains existing population data, predicts population growth according to a linear regression model, obtains prediction results, obtains optimization thresholds of a water supply system, compares the prediction results with the optimization thresholds, obtains comparison results, determines whether the water supply system is optimized according to the comparison results, selects a specific optimization method according to the prediction results, obtains historical weather information, predicts weather change data according to the weather information, predicts hydrological variables according to the weather change data, the hydrological variables include precipitation and evaporation, optimizes a water supply scheduling method according to the hydrological variables, obtains an optimization method, selects an optimization method according to the water supply scheduling method, obtains water plant data, the water plant data includes water supply capacity and water supply safety margin, optimizes water supply plant operation management according to the water supply capacity, the operation management includes water supply scheduling, operation load management, water source allocation, pipe network pressure control, equipment maintenance and emergency plans, and solves the problem that the existing cities have unclear overall planning of water allocation and water use and have no effective basis. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 A flow chart of a method for calculating and analyzing daily water consumption based on data provided by an embodiment of the present invention; Figure 2 A flowchart of the steps of predicting population growth based on existing data and determining whether a water supply system is optimized based on the prediction results provided by an embodiment of the present invention; Figure 3 A flowchart of the steps of predicting hydrological variables according to weather change data and optimizing the water supply scheduling method according to the hydrological variables provided in an embodiment of the present invention; Figure 4 A flowchart of the steps of obtaining water plant data and optimizing water plant operation management according to water supply capacity provided by an embodiment of the present invention; Figure 5 An architecture diagram of a data-based daily water consumption calculation and analysis system provided in an embodiment of the present invention; Figure 6 An architectural diagram of a water supply optimization module provided in an embodiment of the present invention; Figure 7 An architectural diagram of a water supply scheduling module provided in an embodiment of the present invention; Figure 8 This is an architecture diagram of the water supply operation module provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0018] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0019] It is understood that the terms "first", "second", etc. used in this application may be used herein to describe various elements, but unless otherwise specified, these elements are not limited by these terms. These terms are only used to distinguish a first element from another element. For example, without departing from the scope of this application, a first xx script may be referred to as a second xx script, and similarly, a second xx script may be referred to as a first xx script.

[0020] like Figure 1 As shown, a method for calculating and analyzing daily water consumption based on data is provided in an embodiment of the present invention, and the method includes: S100, obtaining historical water supply data of the city, obtaining current data of the city, wherein the current data includes population and water supply system.

[0021] In this step, the historical water supply data of the city is obtained. The historical water supply data refers to the water supply records of the city in the past period of time, including the total water supply, water use structure, peak water supply and water supply loss, such as the average daily water supply, monthly water supply and annual water supply in the past 5-30 years, which are divided into residential water use, industrial water use, commercial water use, agricultural water use and municipal water use; Obtain the existing data of the city, including the population size and water supply system. The future population can be predicted by the current population size. The water consumption can be inferred from the future population, and the future water supply demand can be calculated. The number of water supply plants and daily processing capacity can be known through the water supply system. The total length of the existing pipeline network, the number of main pipelines and branches can be known to ensure sufficient water resources, optimize water source scheduling, evaluate water transmission capacity, and optimize pipeline scheduling.

[0022] S200, predicting population growth based on existing data, obtaining prediction results, judging whether the water supply system is optimized based on the prediction results, obtaining an optimization method, and selecting a specific optimization method based on the prediction results.

[0023] In this step, the population growth is predicted based on the existing data, and the population growth is predicted based on the linear regression model. The linear regression model P t+n =P t +r×n, obtain the prediction results, and judge whether the water supply system is optimized according to the prediction results. If optimization is required, the optimization method needs to be obtained; Optimization methods include ring layout of water supply network, remote control of pipeline valves and dynamic adjustment of water supply. Specific optimization methods are selected based on the prediction results, such as different treatment methods when pipelines are damaged and demand fluctuates. Analyze future water demand based on predicted population data and select appropriate water supply optimization strategies: If the water supply capacity is sufficient (water supply capacity > predicted demand): optimize water supply scheduling and improve water delivery efficiency, such as adjusting the water plant operation mode, optimizing pipeline network pressure control, etc.

[0024] If the water supply capacity is close to the critical value (water supply capacity ≈ predicted demand): strengthen the management of backup water sources, such as increasing groundwater extraction and recycled water utilization, to improve the water supply safety margin.

[0025] If the water supply capacity is insufficient (water supply capacity < predicted demand): expand the water plant, improve water intake, treatment and water transmission capacity, and at the same time optimize the water supply network to reduce water transmission losses.

[0026] For example, a city currently has a daily water supply capacity of 500,000 cubic meters, but it is predicted that the population will increase by 10% in five years and the water demand will increase to 550,000 cubic meters per day. At this time, the following optimization measures can be taken: Short-term optimization: Improve water supply efficiency by 5%-10% by optimizing the water delivery capacity of the pipeline network, reducing leakage, and adjusting water supply scheduling.

[0027] Long-term optimization: Expand the water plant and increase water treatment capacity by 10% to ensure that future water demand is met; The optimization of water supply scheduling methods based on hydrological variables includes increasing reservoir water storage, reducing groundwater extraction, and improving water resource utilization when there is sufficient precipitation (flood season).

[0028] When precipitation decreases (dry season): give priority to using groundwater or backup water sources, reduce unnecessary water use, and increase water supply safety margin.

[0029] When evaporation increases (hot season): reduce water supply during the day, increase water supply at night, and reduce water resource loss.

[0030] For example, a city predicts that precipitation will decrease by 15% in the next two years, while evaporation will increase by 10%, which may cause the reservoir water level to drop by 5-8%. Optimization measures include: Increase water supply at night, reduce evaporation losses during the day, and improve water resource utilization efficiency.

[0031] Reduce pipeline leakage, optimize pipeline pressure control, and reduce water transmission losses by 3-5%.

[0032] Activate alternative water sources, such as inter-regional water transfer, to alleviate water shortages.

[0033] S300, obtaining historical weather information, predicting weather change data according to the weather information, predicting hydrological variables according to the weather change data, and optimizing the water supply scheduling method according to the hydrological variables.

[0034] In this step, historical weather information is obtained. The urban water supply system is greatly affected by weather changes and hydrological variables. Reasonable prediction of weather changes and hydrological variables, such as precipitation and evaporation, can optimize the water supply scheduling method and improve water supply efficiency. Weather change data can be predicted based on weather information, hydrological variables can be predicted based on weather change data, precipitation recharge, evaporation loss and available water resources can be calculated, and the water supply scheduling method can be optimized based on hydrological variables. A ring layout of the water supply network, remote control of pipeline valves and dynamic adjustment of water supply can be adopted.

[0035] S400, obtaining water plant data, wherein the water plant data includes water supply capacity and water supply safety margin, wherein the water supply capacity includes water intake capacity, treatment capacity and water transmission capacity, and optimizing water plant operation management according to the water supply capacity.

[0036] In this step, water plant data is obtained. The operation and management of water plants depends on water supply capacity and water supply safety margin. Water supply capacity includes water intake capacity, treatment capacity and water transmission capacity, while water supply safety margin is a key indicator to ensure the response to emergencies. Water supply safety margin refers to the redundancy of water supply capacity relative to the current water supply demand to ensure that the water supply system can respond to emergencies, such as extreme weather, equipment failure, etc. Water supply safety margin is usually set at 10%-20% of water supply demand; Optimize the operation and management of water supply plants according to water supply capacity. For water intake capacity management, increase water intake when precipitation is sufficient, reduce water intake during the dry season, add backup reservoirs or groundwater wells, and provide additional water sources in emergency situations. For treatment capacity management, high-efficiency filtration and membrane treatment technologies can be used to improve the treatment capacity of water plants. For water transmission capacity management, booster pumps can be adjusted during peak hours to improve remote water supply capacity. Reduce pipe network pressure at night to reduce pipeline losses.

[0037] like Figure 2 As shown, as a preferred embodiment of the present invention, the steps of predicting population growth according to existing data, obtaining prediction results, judging whether the water supply system is optimized according to the prediction results, obtaining an optimization method, and selecting a specific optimization method according to the prediction results specifically include: S201, obtaining the current population data, and predicting the population growth according to the linear regression model. The linear regression model P t+n =P t +r×n.

[0038] In this step, the current population data is obtained. Population growth forecast is a key factor in the planning and optimization of urban water supply systems. By predicting future population growth, future water supply demand can be estimated. Population growth can be predicted based on the linear regression model; Linear regression model P t+n =P t+r×n, where P t is the current population, r is the average annual growth rate, n is the number of predicted years, P t+n is the total population predicted at a certain point in the future, that is, after n years; For example, the current population P t =500000, for example, the urban population in 2020 is 500,000; the average annual growth rate r=7000, which means that the population increases by 7,000 people each year; the number of forecast years n=5, and we want to predict the urban population in 2025; According to the formula: P 2025 =P 2020 +r×(2025-2020); P 2025 =500000+7000×5=500000+35000=535000; So it is predicted that by 2025, the city's population will be 535,000.

[0039] S202, obtaining prediction results, obtaining water supply system optimization thresholds, comparing the prediction results with the optimization thresholds, and obtaining comparison results.

[0040] In this step, the forecast results are obtained, which usually include the impact of factors such as population growth, water demand, and climate change on water resources. The total population in a certain year in the future is predicted using a linear regression model, and then the estimated water demand is obtained by combining the per capita water consumption; Obtain the water supply system optimization threshold, which refers to the minimum standard or maximum load value of a system when meeting water supply demand. When the system operation is close to this threshold, optimization may be required, such as increasing water supply capacity, improving pipe network design, and increasing water treatment plant processing capacity. The threshold can be set based on the upper limit of existing infrastructure capacity or historical experience; The water supply system optimization threshold is set at 150,000,000 liters / day. For example, the daily water supply capacity of the existing water supply system is 120,000,000 liters / day. Therefore, the current capacity of the water supply system is close to the threshold and there is a risk of insufficient water supply.

[0041] S203, judging whether the water supply system is optimized according to the comparison results, and selecting a specific optimization method according to the prediction results.

[0042] In this step, it is determined whether the water supply system is optimized based on the comparison results. If the comparison results show that the predicted water demand is higher than the water supply capacity threshold, the water supply system needs to be optimized. If the comparison results show that the predicted water demand is lower than or equal to the water supply capacity threshold, the system does not need to be optimized. Select specific optimization methods based on the prediction results. The optimization methods include ring layout of water supply network, remote control of pipeline valves and dynamic adjustment of water supply. The ring layout of water supply network refers to designing water supply pipelines into a ring structure so that water flow can bypass the entire water supply area, enhancing the stability and flexibility of the water supply system. The ring layout can effectively avoid the problem of the entire system being paralyzed when a single pipeline fails, and improve the scheduling flexibility of water sources; The pipeline valve remote control system uses automated control technology to dynamically adjust the water supply system by real-time monitoring and adjusting the valves in the water supply network. By remotely controlling the valves, it can respond quickly in emergency situations and adjust the water supply path and flow to avoid water supply interruption or waste; Dynamic adjustment of water supply refers to the flexible adjustment of water supply and water supply strategy based on real-time monitored water demand, meteorological data, reservoir water level and other information. This method can flexibly respond to demand fluctuations, optimize the allocation of water supply resources, and avoid waste or shortages; When a problem occurs in a pipeline, the water supply of the entire area will be affected. With the ring layout, water can flow in multiple directions in the pipe network. When water supply demand fluctuates or in emergencies, such as sudden water source problems or pipeline leaks, the system can adjust the water supply direction and water flow through remote control valves, optimize water supply efficiency and reduce unnecessary water losses. Dynamic adjustment of water supply is very suitable for responding to sudden demand fluctuations or climate changes.

[0043] like Figure 3 As shown, as a preferred embodiment of the present invention, the steps of obtaining historical weather information, predicting weather change data according to the weather information, predicting hydrological variables according to the weather change data, and optimizing the water supply scheduling method according to the hydrological variables specifically include: S301, obtaining historical weather information, and predicting weather change data according to the weather information, wherein the weather change data includes temperature and precipitation.

[0044] In this step, to obtain historical weather information, it is necessary to collect historical weather data from the past 10 to 30 years. These data mainly include information such as average annual temperature, maximum temperature, minimum temperature, precipitation, humidity, wind speed, and sunshine duration. Changes in temperature determine the evaporation of water resources, while changes in precipitation directly affect the replenishment of water sources. In addition, relative humidity, wind speed, and sunshine duration are also important factors that affect changes in temperature and precipitation; Predict weather change data based on weather information. Weather change data includes temperature and precipitation. Temperature changes usually have the characteristics of long-term trends and seasonal fluctuations. By analyzing past temperature data, it can be found whether there is a clear upward or downward trend in temperature changes. Generally speaking, the average temperature of a city will rise slowly with global climate change, while the temperature in a local area may be affected by factors such as urbanization and changes in the surface environment; Changes in precipitation are more complex than temperature and are affected by many factors, including global climate change, atmospheric circulation, and topography. For a city, historical precipitation data can reveal interannual changes and seasonal fluctuations in precipitation. For example, the rainy season in a city may be concentrated from May to September each year, while precipitation is less in other months. By analyzing past precipitation data, it is possible to predict the changing trend of precipitation in the next few years.

[0045] S302, predicting hydrological variables according to weather change data, wherein the hydrological variables include precipitation and evaporation.

[0046] In this step, hydrological variables are predicted based on weather change data. Hydrological variables are key factors in water supply management, among which precipitation and evaporation determine the supply and consumption of water resources. By analyzing weather change data, future precipitation and evaporation can be predicted, thereby optimizing water resource management; Precipitation is mainly affected by temperature, humidity, wind speed, atmospheric pressure and cloudiness. Generally speaking, rising temperatures may lead to more water evaporation, thereby increasing the probability of precipitation, but extreme high temperatures may also inhibit precipitation. Air with higher humidity is more likely to form precipitation, while dry climates usually have less precipitation. Wind speed and direction affect the transport of water vapor, thereby changing the distribution of precipitation. Changes in atmospheric pressure affect the formation of precipitation, and low-pressure systems are usually accompanied by more precipitation. Evaporation is mainly affected by temperature, wind speed, humidity, solar radiation and air pressure. Generally speaking, rising temperature will accelerate water evaporation. When the wind speed is high, the water on the water surface is more easily carried away, increasing the evaporation rate. Air with lower humidity can hold more water vapor, thereby promoting evaporation. The duration of sunshine and solar radiation determine the degree of surface heating, thereby affecting the evaporation.

[0047] S303, optimizing the water supply scheduling mode according to the hydrological variables, wherein the water supply scheduling mode includes unified scheduling water supply, zone scheduling water supply and time-sharing scheduling water supply, obtaining an optimization method, and selecting the optimization method according to the water supply scheduling mode.

[0048] In this step, the water supply scheduling method is optimized according to the hydrological variables. When the precipitation decreases, the available water resources decrease and the water supply system faces pressure. When the evaporation increases, the water loss in water sources such as reservoirs increases. The water supply scheduling methods include unified scheduling water supply, zoned scheduling water supply and time-sharing scheduling water supply. Unified scheduling water supply is suitable for the situation where water resources are generally sufficient but the water supply efficiency needs to be optimized. Zoned scheduling water supply is suitable for the situation where water resources are unevenly distributed and water supply demand varies in different regions. Time-sharing scheduling water supply is suitable for the situation where water supply demand fluctuates greatly in different time periods.

[0049] Obtain optimization methods. When the overall water resources are stable but there is a problem of low water supply efficiency, it is necessary to optimize unified scheduling to improve the water supply capacity and distribution efficiency of the water plant. The optimization methods include intelligent water supply system: introduce intelligent water supply management system, monitor hydrological variables in real time, and dynamically adjust the water supply; optimize water plant production capacity: when the precipitation is predicted to decrease, increase the reservoir storage capacity in advance and improve the water plant processing capacity; optimize reservoir scheduling: when precipitation is abundant, reserve water sources, and reasonably allocate water when precipitation is less to avoid waste.

[0050] like Figure 4 As shown, as a preferred embodiment of the present invention, the water plant data is obtained, the water plant data includes water supply capacity and water supply safety margin, the water supply capacity includes water intake capacity, processing capacity and water transmission capacity, and the steps of optimizing the operation and management of the water supply plant according to the water supply capacity specifically include: S401, obtaining water plant data, wherein the water plant data includes water supply capacity and water supply safety margin.

[0051] In this step, water plant data is obtained. The operation and management of water plants depends on water supply capacity and water supply safety margin. Water supply capacity includes water intake capacity, treatment capacity and water transmission capacity, while water supply safety margin is a key indicator to ensure emergency response. Water supply safety margin refers to the redundancy of water supply capacity relative to current water supply demand to ensure that the water supply system can respond to emergencies, such as extreme weather, equipment failure, etc. Water supply safety margin is usually set at 10%-20% of water supply demand.

[0052] S402: Water supply capacity includes water intake capacity, treatment capacity and water transmission capacity. The water supply safety margin is the additional water supply capacity.

[0053] In this step, water supply capacity includes water intake capacity, treatment capacity and water delivery capacity. Water intake capacity refers to the maximum amount of water that a water plant can extract from a water source every day, such as rivers, reservoirs, groundwater and desalination plants. Its size depends on factors such as the availability of water sources, the capacity of water intake pumping stations and water intake permits; treatment capacity refers to the amount of water that a water plant can process and supply every day that meets water quality standards, which is affected by water treatment technology, equipment efficiency and water source water quality factors; water delivery capacity refers to the maximum amount of water that a water plant can deliver to the user end through the water delivery network every day, which is affected by the network delivery capacity, water pressure regulation and leakage rate; Water supply safety margin refers to the amount of water that a water plant can provide in addition to meeting the current water supply demand to cope with emergencies. Usually, the water supply safety margin is set at 10%-20% of the water supply demand to ensure stable water supply; Water supply safety margin = (total water supply capacity − current water supply demand) / current water supply demand × 100%; For example, the current water demand is 400,000 cubic meters per day, and the total water supply capacity is 480,000 cubic meters per day; Calculate the water supply safety margin: (480,000-400,000) / 400,000×100%=20%; The current water supply safety margin is 20%, which is within the safe range and the system can cope with sudden increases in demand.

[0054] S403, optimizing the operation management of the water supply plant according to the water supply capacity, wherein the operation management includes water supply scheduling, operation load management, water source allocation, pipe network pressure control, equipment maintenance and emergency plans.

[0055] In this step, the operation and management of the water supply plant is optimized according to the water supply capacity. The operation and management includes water supply scheduling, operation load management, water source allocation, pipe network pressure control, equipment maintenance and emergency plans to ensure the stability and safety of the water supply system. Water supply scheduling refers to dynamically adjusting water supply and water distribution strategies based on real-time water demand, water supply capacity, weather conditions and reservoir water levels to ensure water supply safety and economy, increase water delivery capacity during peak water use periods, reduce water delivery pressure during low-water periods at night to reduce pipe network losses, reduce dependence on surface water during dry seasons, and increase the use of groundwater or unconventional water sources; The operation load management of the water supply plant aims to reasonably allocate the production capacity of the water plant, avoid overload operation of equipment, improve energy utilization efficiency, and reduce operating costs. The operation load management is optimized for multiple water plants to operate in time, avoid long-term high-load operation of a single water plant, and adjust the operation load of the water plant during periods of low water demand to reduce unnecessary water treatment. Water source allocation refers to the reasonable allocation of water intake between different water sources to ensure the sustainability of water sources and reduce the risk of water shortage. The optimization measures are to combine surface water and groundwater, dynamically adjust the water intake, increase reservoir water storage in the flood season according to the forecast of precipitation and evaporation, improve groundwater utilization in the dry season, establish a backup reservoir and deep groundwater extraction system to deal with sudden water shortages. The stability of the water supply system of the water plant depends on the balance of pipe network pressure. Excessive water pressure may cause pipe bursts, while too low water pressure may lead to insufficient water supply. The optimization measures for pipe network pressure control are to install remote monitoring sensors, monitor the water pressure in each area in real time, and adjust the operation mode of the booster pump. The equipment maintenance of the water supply plant is directly related to the stability and operation cost of the system. A reasonable maintenance plan can reduce equipment failures, extend equipment life, and improve water supply safety; an emergency plan is a response strategy for the water supply system when facing emergencies, such as extreme weather, pipe ruptures, and pollution accidents, to ensure that water supply is not interrupted in an emergency.

[0056] like Figure 5 As shown, a data-based daily water consumption calculation and analysis system provided by an embodiment of the present invention includes: The basic information module 100 is used to obtain the historical water supply data of the city and the current data of the city, wherein the current data includes the population and the water supply system.

[0057] In this system, the basic information module 100 obtains the historical water supply data of the city. The historical water supply data refers to the water supply records of the city in the past period of time, including the total water supply, water use structure, peak water supply and water supply loss, such as the average daily water supply, average monthly water supply and average annual water supply in the past 5-30 years, which are divided into residential water use, industrial water use, commercial water use, agricultural water use and municipal water use by category; Obtain the existing data of the city, including the population size and water supply system. The future population can be predicted by the current population size. The water consumption can be inferred from the future population, and the future water supply demand can be calculated. The number of water supply plants and daily processing capacity can be known through the water supply system. The total length of the existing pipeline network, the number of main pipelines and branches can be known to ensure sufficient water resources, optimize water source scheduling, evaluate water transmission capacity, and optimize pipeline scheduling.

[0058] The water supply optimization module 200 is used to predict population growth based on existing data, obtain prediction results, determine whether the water supply system is optimized based on the prediction results, obtain optimization methods, and select specific optimization methods based on the prediction results.

[0059] In this system, the water supply optimization module 200 predicts population growth based on existing data and predicts population growth based on a linear regression model. t+n =P t +r×n, obtain the prediction results, and judge whether the water supply system is optimized according to the prediction results. If optimization is required, the optimization method needs to be obtained; Optimization methods include ring layout of water supply network, remote control of pipeline valves and dynamic adjustment of water supply. Specific optimization methods are selected based on the prediction results. For example, different treatment methods are selected when pipelines are damaged and demand fluctuates.

[0060] The water supply scheduling module 300 is used to obtain historical weather information, predict weather change data based on the weather information, predict hydrological variables based on the weather change data, and optimize the water supply scheduling method based on the hydrological variables.

[0061] In this system, the water supply scheduling module 300 obtains historical weather information. The urban water supply system is greatly affected by weather changes and hydrological variables. Reasonable prediction of weather changes and hydrological variables, such as precipitation and evaporation, can optimize the water supply scheduling method and improve water supply efficiency; Weather change data can be predicted based on weather information, hydrological variables can be predicted based on weather change data, precipitation recharge, evaporation loss and available water resources can be calculated, and the water supply scheduling method can be optimized based on hydrological variables. A ring layout of the water supply network, remote control of pipeline valves and dynamic adjustment of water supply can be adopted.

[0062] The water supply operation module 400 is used to obtain water plant data, which includes water supply capacity and water supply safety margin. The water supply capacity includes water intake capacity, processing capacity and water transmission capacity, and optimizes the operation management of the water supply plant according to the water supply capacity.

[0063] In this system, the water supply operation module 400 obtains water plant data. The operation and management of the water plant depends on the water supply capacity and water supply safety margin. The water supply capacity includes water intake capacity, treatment capacity and water transmission capacity, while the water supply safety margin is a key indicator to ensure the response to emergencies. The water supply safety margin refers to the redundancy of the water supply capacity relative to the current water supply demand to ensure that the water supply system can respond to emergencies, such as extreme weather, equipment failure, etc. The water supply safety margin is usually set at 10%-20% of the water supply demand; Optimize the operation and management of water supply plants according to water supply capacity. For water intake capacity management, increase water intake when precipitation is sufficient, reduce water intake during the dry season, add backup reservoirs or groundwater wells, and provide additional water sources in emergency situations. For treatment capacity management, high-efficiency filtration and membrane treatment technologies can be used to improve the treatment capacity of water plants. For water transmission capacity management, booster pumps can be adjusted during peak hours to improve remote water supply capacity. Reduce pipe network pressure at night to reduce pipeline losses.

[0064] like Figure 6 As shown, as a preferred embodiment of the present invention, the water supply optimization module 200 includes: The population prediction unit 201 is used to obtain the current population data and predict the population growth according to the linear regression model. t+n =P t +r×n.

[0065] In this module, the population prediction unit 201 obtains the current population data. In the process of urban water supply system planning and optimization, population growth prediction is a key factor. By predicting future population growth, the future water supply demand can be estimated. The population growth can be predicted based on the linear regression model; Linear regression model P t+n =P t +r×n, where P t is the current population, r is the average annual growth rate, n is the number of predicted years, P t+n is the total population predicted at a certain point in the future, that is, after n years; For example, the current population P t =500000, for example, the urban population in 2020 is 500,000; the average annual growth rate r=7000, which means that the population increases by 7,000 people each year; the number of forecast years n=5, and we want to predict the urban population in 2025; According to the formula: P 2025 =P 2020 +r×(2025-2020); P 2025 =500000+7000×5=500000+35000=535000; So it is predicted that by 2025, the city's population will be 535,000.

[0066] The comparison unit 202 is used to obtain the prediction result, obtain the optimization threshold of the water supply system, compare the prediction result with the optimization threshold, and obtain the comparison result.

[0067] In this module, the comparison unit 202 obtains the prediction results, which usually include the impact of factors such as population growth, water demand, and climate change on water resources, and uses a linear regression model to predict the total population in a future year, and then combines the per capita water consumption to obtain the expected water demand; Obtain the water supply system optimization threshold, which refers to the minimum standard or maximum load value of a system when meeting water supply demand. When the system operation is close to this threshold, optimization may be required, such as increasing water supply capacity, improving pipe network design, and increasing water treatment plant processing capacity. The threshold can be set based on the upper limit of existing infrastructure capacity or historical experience; The water supply system optimization threshold is set to 150,000,000 liters / day. For example, the daily water supply capacity of the existing water supply system is 120,000,000 liters / day. Therefore, the current capacity of the water supply system is close to the threshold and there is a risk of insufficient water supply.

[0068] The water supply optimization unit 203 is used to determine whether the water supply system is optimized according to the comparison results and select a specific optimization method according to the prediction results.

[0069] In this module, the water supply optimization unit 203 determines whether the water supply system is optimized according to the comparison result. If the comparison result shows that the predicted water demand is higher than the water supply capacity threshold, the water supply system needs to be optimized. If the comparison result shows that the predicted water demand is lower than or equal to the water supply capacity threshold, the system does not need to be optimized. Select specific optimization methods based on the prediction results. The optimization methods include ring layout of water supply network, remote control of pipeline valves and dynamic adjustment of water supply. The ring layout of water supply network refers to designing water supply pipelines into a ring structure so that water flow can bypass the entire water supply area, enhancing the stability and flexibility of the water supply system. The ring layout can effectively avoid the problem of the entire system being paralyzed when a single pipeline fails, and improve the scheduling flexibility of water sources; The pipeline valve remote control system uses automatic control technology to achieve dynamic adjustment of the water supply system by real-time monitoring and adjusting the valves in the water supply network. By remotely controlling the valves, it is possible to respond quickly in an emergency and adjust the water supply path and flow to avoid water supply interruption or waste; dynamic adjustment of water supply refers to the flexible adjustment of water supply and water supply strategy based on real-time monitored water demand, meteorological data, reservoir water level and other information. This method can flexibly respond to demand fluctuations, optimize the allocation of water supply resources, and avoid waste or shortages; when a pipeline has problems, the water supply of the entire area will be affected. Through the ring layout, water flow can have multiple directions in the pipeline network. When water supply demand fluctuates or emergencies occur, such as sudden water source problems or pipeline leaks, the system can adjust the water supply direction and water flow through remote control valves, optimize water supply efficiency and reduce unnecessary water losses. Dynamic adjustment of water supply is very suitable for responding to sudden demand fluctuations or climate change.

[0070] like Figure 7 As shown, as a preferred embodiment of the present invention, the water supply scheduling module 300 includes: The weather unit 301 is used to obtain historical weather information and predict weather change data based on the weather information, wherein the weather change data includes temperature and precipitation.

[0071] In this module, the weather unit 301 obtains historical weather information and needs to collect historical weather data from the past 10 to 30 years. These data mainly include information such as average annual temperature, maximum temperature, minimum temperature, precipitation, humidity, wind speed, and sunshine duration. Changes in temperature determine the evaporation of water resources, while changes in precipitation directly affect the replenishment of water sources. In addition, relative humidity, wind speed, and sunshine duration are also important factors that affect changes in temperature and precipitation; Predict weather change data based on weather information. Weather change data includes temperature and precipitation. Temperature changes usually have the characteristics of long-term trends and seasonal fluctuations. By analyzing past temperature data, it can be found whether there is a clear upward or downward trend in temperature changes. Generally speaking, the average temperature of a city will rise slowly with global climate change, while the temperature in a local area may be affected by factors such as urbanization and changes in the surface environment; Changes in precipitation are more complex than temperature and are affected by many factors, including global climate change, atmospheric circulation, and topography. For a city, historical precipitation data can reveal interannual changes and seasonal fluctuations in precipitation. For example, the rainy season in a city may be concentrated from May to September each year, while precipitation is less in other months. By analyzing past precipitation data, it is possible to predict the changing trend of precipitation in the next few years.

[0072] The hydrological variable unit 302 is used to predict hydrological variables according to weather change data, and the hydrological variables include precipitation and evaporation.

[0073] In this module, the hydrological variable unit 302 predicts hydrological variables based on weather change data. Hydrological variables are key factors in water supply management, among which precipitation and evaporation determine the supply and consumption of water resources. By analyzing weather change data, future precipitation and evaporation can be predicted, thereby optimizing water resource management; Precipitation is mainly affected by temperature, humidity, wind speed, atmospheric pressure and cloudiness. Generally speaking, rising temperatures may lead to more water evaporation, thereby increasing the probability of precipitation, but extreme high temperatures may also inhibit precipitation. Air with higher humidity is more likely to form precipitation, while dry climates usually have less precipitation. Wind speed and direction affect the transport of water vapor, thereby changing the distribution of precipitation. Changes in atmospheric pressure affect the formation of precipitation, and low-pressure systems are usually accompanied by more precipitation. Evaporation is mainly affected by temperature, wind speed, humidity, solar radiation and air pressure. Generally speaking, rising temperature will accelerate water evaporation. When the wind speed is high, the water on the water surface is more easily carried away, increasing the evaporation rate. Air with lower humidity can hold more water vapor, thereby promoting evaporation. The duration of sunshine and solar radiation determine the degree of surface heating, thereby affecting the evaporation.

[0074] The water supply scheduling unit 303 is used to optimize the water supply scheduling mode according to the hydrological variables, the water supply scheduling mode includes unified scheduling water supply, zone scheduling water supply and time-sharing scheduling water supply, obtain the optimization method, and select the optimization method according to the water supply scheduling mode.

[0075] In this module, the water supply scheduling unit 303 optimizes the water supply scheduling mode according to the hydrological variables. When the precipitation decreases, the available water resources decrease, and the water supply system faces pressure. When the evaporation increases, the water loss in water sources such as reservoirs increases. Water supply scheduling methods include unified scheduling, zone scheduling and time-sharing scheduling. Unified scheduling is suitable for situations where water resources are generally sufficient but the water supply efficiency needs to be optimized. Zone scheduling is suitable for situations where water resources are unevenly distributed and water supply demand varies in different regions. Time-sharing scheduling is suitable for situations where water supply demand fluctuates greatly in different time periods.

[0076] Obtain optimization methods. When the overall water resources are stable but there is a problem of low water supply efficiency, it is necessary to optimize unified scheduling to improve the water supply capacity and distribution efficiency of the water plant. The optimization methods include intelligent water supply system: introducing intelligent water supply management system, real-time monitoring of hydrological variables, and dynamic adjustment of water supply; Optimize water plant capacity: When precipitation is predicted to decrease, increase reservoir storage capacity in advance and improve water plant processing capacity; Optimize reservoir scheduling: reserve water when there is abundant rainfall, and allocate it reasonably when there is less rainfall to avoid waste.

[0077] like Figure 8 As shown, as a preferred embodiment of the present invention, the water supply operation module 400 includes: The water plant unit 401 is used to obtain water plant data, wherein the water plant data includes water supply capacity and water supply safety margin.

[0078] In this module, the water plant unit 401 obtains water plant data. The operation and management of the water plant depends on the water supply capacity and water supply safety margin. The water supply capacity includes water intake capacity, treatment capacity and water transmission capacity, while the water supply safety margin is a key indicator to ensure the response to emergencies. The water supply safety margin refers to the redundancy of the water supply capacity relative to the current water supply demand to ensure that the water supply system can respond to emergencies, such as extreme weather, equipment failure, etc. The water supply safety margin is usually set at 10%-20% of the water supply demand.

[0079] The water supply capacity unit 402 is used for water supply capacity including water intake capacity, treatment capacity and water transmission capacity, and the water supply safety margin is the additional water supply capacity.

[0080] In this module, the water supply capacity unit 402 includes water intake capacity, treatment capacity and water delivery capacity. Water intake capacity refers to the maximum amount of water that a water plant can extract from a water source every day, such as rivers, reservoirs, groundwater and seawater desalination plants. Its size depends on factors such as the availability of water sources, the capacity of water intake pumping stations and water intake permits; treatment capacity refers to the amount of water that a water plant can process and supply every day that meets water quality standards, which is affected by water treatment technology, equipment efficiency and water source water quality factors; water delivery capacity refers to the maximum amount of water that a water plant can deliver to the user end through the water delivery network every day, which is affected by the network delivery capacity, water pressure regulation and leakage rate; Water supply safety margin refers to the amount of water that a water plant can provide in addition to meeting the current water supply demand to cope with emergencies. Usually, the water supply safety margin is set at 10%-20% of the water supply demand to ensure stable water supply; Water supply safety margin = (total water supply capacity − current water supply demand) / current water supply demand × 100%; For example, the current water supply demand is 400,000 cubic meters per day, and the total water supply capacity is 480,000 cubic meters per day; Calculate the water supply safety margin: (480,000-400,000) / 400,000×100%=20%; The current water supply safety margin is 20%, which is within the safe range and the system can cope with sudden increases in demand.

[0081] The water supply operation unit 403 is used to optimize the operation management of the water supply plant according to the water supply capacity. The operation management includes water supply scheduling, operation load management, water source allocation, pipe network pressure control, equipment maintenance and emergency plans.

[0082] In this module, the water supply operation unit 403 optimizes the operation management of the water supply plant according to the water supply capacity. The operation management includes water supply scheduling, operation load management, water source allocation, pipe network pressure control, equipment maintenance and emergency plans to ensure the stability and safety of the water supply system; Water supply scheduling refers to dynamically adjusting water supply and water distribution strategies based on real-time water demand, water supply capacity, weather conditions and reservoir water levels to ensure water supply safety and economy, increase water delivery capacity during peak water use periods, reduce water delivery pressure during low-water periods at night to reduce pipe network losses, reduce dependence on surface water during dry seasons, and increase the use of groundwater or unconventional water sources; The operation load management of water supply plants aims to reasonably allocate the production capacity of water plants, avoid overload operation of equipment, improve energy efficiency, and reduce operating costs. The operation load management is optimized for multiple water plants to operate in different time periods, avoid long-term high-load operation of a single water plant, and adjust the operation load of water plants during periods of low water demand to reduce unnecessary water treatment volume. Water source allocation refers to the reasonable allocation of water intake between different water sources to ensure the sustainability of water sources and reduce the risk of water shortage. The optimization measures are to combine surface water and groundwater, dynamically adjust water intake, increase reservoir water storage in the flood season, improve groundwater utilization in the dry season according to precipitation and evaporation forecasts, establish backup reservoirs and deep groundwater extraction systems to cope with sudden water shortages; the stability of the water supply system of the water plant depends on the balance of pipe network pressure. Excessive water pressure may cause pipe bursts, while too low water pressure may lead to insufficient water supply. The optimization measures for pipe network pressure control are to install remote monitoring sensors, monitor the water pressure in each area in real time, and adjust the booster pump operation mode; the equipment maintenance of the water supply plant is directly related to the stability and operating cost of the system. A reasonable maintenance plan can reduce equipment failures, extend equipment life, and improve water supply safety; the emergency plan is the response strategy of the water supply system in the face of emergencies, such as extreme weather, pipe ruptures, and pollution accidents, to ensure that water supply is not interrupted in an emergency.

[0083] In one embodiment, a computer device is provided, the computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the following steps are implemented: Obtaining historical water supply data of the city and obtaining current data of the city, wherein the current data includes population and water supply system; Predict population growth based on existing data, obtain prediction results, determine whether the water supply system is optimized based on the prediction results, obtain optimization methods, and select specific optimization methods based on the prediction results; Obtain historical weather information, predict weather change data based on the weather information, predict hydrological variables based on the weather change data, and optimize the water supply scheduling method based on the hydrological variables; Acquire water plant data, wherein the water plant data includes water supply capacity and water supply safety margin, wherein the water supply capacity includes water intake capacity, treatment capacity and water transmission capacity, and optimize the operation and management of the water supply plant according to the water supply capacity.

[0084] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the processor performs the following steps: Obtaining historical water supply data of the city and obtaining current data of the city, wherein the current data includes population and water supply system; Predict population growth based on existing data, obtain prediction results, determine whether the water supply system is optimized based on the prediction results, obtain optimization methods, and select specific optimization methods based on the prediction results; Obtain historical weather information, predict weather change data based on the weather information, predict hydrological variables based on the weather change data, and optimize the water supply scheduling method based on the hydrological variables; Acquire water plant data, wherein the water plant data includes water supply capacity and water supply safety margin, wherein the water supply capacity includes water intake capacity, treatment capacity and water transmission capacity, and optimize the operation and management of the water supply plant according to the water supply capacity.

[0085] It should be understood that, although each step in the flow chart of each embodiment of the present invention is shown in sequence according to the indication of the arrow, these steps are not necessarily performed in sequence according to the order indicated by the arrow. Unless there is a clear explanation in this article, the execution of these steps does not have a strict order restriction, and these steps can be performed in other orders. Moreover, at least a portion of the steps in each embodiment may include a plurality of sub-steps or a plurality of stages, and these sub-steps or stages are not necessarily performed at the same time, but can be performed at different times, and the execution order of these sub-steps or stages is not necessarily performed in sequence, but can be performed in turn or alternately with at least a portion of other steps or sub-steps or stages of other steps.

[0086] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the program can be stored in a non-volatile computer-readable storage medium. When the program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0087] The technical features of the above-described embodiments may be arbitrarily combined. To make the description concise, not all possible combinations of the technical features in the above-described embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0088] The above-mentioned embodiments only express several implementation methods of the present invention, and the description thereof is relatively specific and detailed, but it cannot be understood as limiting the scope of the patent of the present invention. It should be pointed out that, for ordinary technicians in this field, several variations and improvements can be made without departing from the concept of the present invention, which all belong to the protection scope of the present invention. Therefore, the protection scope of the patent of the present invention shall be subject to the attached claims.

[0089] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for calculating and analyzing daily water consumption based on data, characterized in that: The method comprises: Obtaining historical water supply data of the city and obtaining current data of the city, wherein the current data includes population and water supply system; Predict population growth based on existing data, obtain prediction results, determine whether the water supply system is optimized based on the prediction results, obtain optimization methods, and select specific optimization methods based on the prediction results; Obtain historical weather information, predict weather change data based on the weather information, predict hydrological variables based on the weather change data, and optimize the water supply scheduling method based on the hydrological variables; Acquire water plant data, wherein the water plant data includes water supply capacity and water supply safety margin, wherein the water supply capacity includes water intake capacity, treatment capacity and water transmission capacity, and optimize the operation and management of the water supply plant according to the water supply capacity.

2. The method for calculating and analyzing daily water consumption based on data according to claim 1, characterized in that: The steps of predicting population growth based on existing data, obtaining prediction results, judging whether the water supply system is optimized based on the prediction results, obtaining an optimization method, and selecting a specific optimization method based on the prediction results specifically include: Obtain the current population data and predict population growth based on the linear regression model. The linear regression model P t+n =P t +r×n; Obtain prediction results, obtain optimization thresholds for the water supply system, compare the prediction results with the optimization thresholds, and obtain comparison results; Determine whether the water supply system is optimized based on the comparison results, and select the specific optimization method based on the prediction results.

3. The method for calculating and analyzing daily water consumption based on data according to claim 1 is characterized in that: The steps of obtaining historical weather information, predicting weather change data according to the weather information, predicting hydrological variables according to the weather change data, and optimizing the water supply scheduling method according to the hydrological variables specifically include: Obtain historical weather information, and predict weather change data based on the weather information, wherein the weather change data includes temperature and precipitation; Predicting hydrological variables based on weather change data, wherein the hydrological variables include precipitation and evaporation; The water supply scheduling method is optimized according to the hydrological variables, and the water supply scheduling method includes unified scheduling water supply, zone scheduling water supply and time-sharing scheduling water supply, and an optimization method is obtained and selected according to the water supply scheduling method.

4. The method for calculating and analyzing daily water consumption based on data according to claim 1 is characterized in that: The step of obtaining water plant data, wherein the water plant data includes water supply capacity and water supply safety margin, wherein the water supply capacity includes water intake capacity, treatment capacity and water transmission capacity, and optimizing the operation and management of the water supply plant according to the water supply capacity specifically includes: Acquiring water plant data, wherein the water plant data includes water supply capacity and water supply safety margin; Water supply capacity includes water intake capacity, treatment capacity and water transmission capacity, and water supply safety margin is the additional water supply capacity; The operation and management of the water supply plant is optimized according to the water supply capacity, and the operation and management includes water supply scheduling, operation load management, water source allocation, pipe network pressure control, equipment maintenance and emergency plans.

5. The method for calculating and analyzing daily water consumption based on data according to claim 2 is characterized in that: The optimization method includes a ring layout of a water supply network, remote control of pipeline valves, and dynamic adjustment of water supply.

6. A data-based daily water consumption calculation and analysis system, characterized in that: The system comprises: The basic information module obtains the historical water supply data of the city and the existing data of the city, wherein the existing data includes the population and the water supply system; The water supply optimization module predicts population growth based on existing data, obtains the prediction results, determines whether the water supply system is optimized based on the prediction results, obtains the optimization method, and selects the specific optimization method based on the prediction results; The water supply scheduling module obtains historical weather information, predicts weather change data based on the weather information, predicts hydrological variables based on the weather change data, and optimizes the water supply scheduling method based on the hydrological variables; The water supply operation module obtains water plant data, which includes water supply capacity and water supply safety margin. The water supply capacity includes water intake capacity, processing capacity and water transmission capacity, and optimizes the operation management of the water supply plant according to the water supply capacity.

7. The data-based daily water consumption calculation and analysis system according to claim 6 is characterized in that: The water supply optimization module comprises: The population prediction unit obtains the current population data and predicts the population growth according to the linear regression model. The linear regression model P t+n =P t +r×n; A comparison unit obtains the prediction result, obtains the optimization threshold of the water supply system, compares the prediction result with the optimization threshold, and obtains the comparison result; The water supply optimization unit determines whether the water supply system is optimized based on the comparison results and selects a specific optimization method based on the prediction results.

8. The data-based daily water consumption calculation and analysis system according to claim 7 is characterized in that: The water supply scheduling module includes: A weather unit, which obtains historical weather information and predicts weather change data based on the weather information, wherein the weather change data includes temperature and precipitation; A hydrological variable unit, which predicts hydrological variables according to weather change data, wherein the hydrological variables include precipitation and evaporation; The water supply scheduling unit optimizes the water supply scheduling mode according to the hydrological variables, wherein the water supply scheduling mode includes unified scheduling water supply, zone scheduling water supply and time-sharing scheduling water supply, obtains the optimization method, and selects the optimization method according to the water supply scheduling mode.

9. The data-based daily water consumption calculation and analysis system according to claim 8, characterized in that: The water supply operation module comprises: A water plant unit, which obtains water plant data, wherein the water plant data includes water supply capacity and water supply safety margin; Water supply capacity unit, water supply capacity includes water intake capacity, treatment capacity and water transmission capacity, and water supply safety margin is the additional water supply capacity; The water supply operation unit optimizes the operation management of the water supply plant according to the water supply capacity. The operation management includes water supply scheduling, operation load management, water source allocation, pipe network pressure control, equipment maintenance and emergency plans.

10. The data-based daily water consumption calculation and analysis system according to claim 9, characterized in that: The optimization method includes a ring layout of a water supply network, remote control of pipeline valves, and dynamic adjustment of water supply.

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