Method, device and equipment for determining resilience index of urban water environment

Abstract

The present invention provides a method, device, and equipment for determining the resilience index of an urban water environment, belonging to the field of urban resilience calculation technology. The method for determining the resilience index of an urban water environment includes: determining the risk level corresponding to each of the M time periods based on hydrological data of a target urban area within M time periods; obtaining a water quality index for each of N predetermined risk levels based on water quality data of the target urban area within the M time periods; and determining the resilience index of the water environment in the target urban area based on the water quality index and hydrological index of each of the N predetermined risk levels. The water environment resilience index determined by the method provided by the present invention is more accurate, practical, and operational.

Description

Technical Field

[0001] The present invention relates to the field of urban resilience calculation technology, and more specifically, to a method, device and equipment for determining the resilience index of an urban water environment. Background Art

[0002] The overall quality of urban water environment is currently showing a trend of continuous improvement, but the problem of pollution during flood season is becoming increasingly prominent. Therefore, it is urgent to calculate the resilience of urban water environment in order to optimize urban ecological infrastructure according to the resilience level of urban water environment and thus cope with flood season pollution.

[0003] In related technologies, the methods for determining the resilience of urban water environments are complex, with poor practicality and operability, and are unable to accurately determine the resilience of urban water environments when facing pollution problems during flood seasons. Summary of the Invention

[0004] In view of this, the present invention provides a method, apparatus, device, medium and program product for determining the resilience index of an urban water environment.

[0005] One aspect of the present invention provides a method for determining the resilience index of an urban water environment, comprising the following steps: determining the risk level corresponding to each of the M time periods based on the hydrological data of a target urban area within M time periods, wherein the risk level corresponding to each time period is one of N predetermined risk levels, and the N predetermined risk levels correspond to N different hydrological indices according to the risk level value, and M and N are each independently integers greater than or equal to 1, and the hydrological data include at least one of precipitation data and sponge project design data; obtaining the water quality index of each of the N predetermined risk levels based on the water quality data of the target urban area within M time periods, wherein the water quality data include the physical and chemical properties data of the water body in the target urban area, and the water quality index is used to characterize the degree of fluctuation of the water environment of the target urban area corresponding to each predetermined risk level; determining the resilience index of the water environment of the target urban area based on the water quality index and hydrological index of each of the N predetermined risk levels.

[0006] According to an embodiment of the present invention, obtaining the water quality index of each of N predetermined risk levels based on the water quality data of the target urban area in M ​​time periods includes performing the following operations for any i-th predetermined risk level, wherein: : Determine at least one target time period corresponding to the i-th predetermined risk level among the M time periods; obtain a water quality score for the target time period based on the water quality data of the target city area within the target time period, wherein water quality data in different concentration ranges correspond to different water quality scores; obtain a maximum water quality score for the M time periods based on the water quality data of the target city area within the M time periods; calculate a water quality index for the i-th predetermined risk level based on the water quality score of the target time period and the maximum water quality score of the M time periods, so as to obtain water quality indices for each of the N predetermined risk levels.

[0007] According to an embodiment of the present invention, the target urban area includes multiple calculation units; obtaining the water quality index of each of N predetermined risk levels based on the water quality data of the target urban area in M ​​time periods includes: for any i-th predetermined risk level, performing the following operations, wherein: : Determine at least one target time period corresponding to the i-th predetermined risk level in the M time periods; obtain a water quality score for each calculation unit in the target time period based on the water quality data of each calculation unit in the target time period, wherein water quality data in different concentration ranges correspond to different water quality scores; obtain a maximum water quality score for each calculation unit in the M time periods based on the water quality data of each calculation unit in the M time periods; calculate a water quality index for each calculation unit in the target time period based on the water quality score of each calculation unit in the target time period and the maximum water quality score of each calculation unit in the M time periods, and obtain water quality indexes of each of the multiple calculation units in the target time period; calculate the water quality index of the i-th predetermined risk level based on the water quality indexes of each of the multiple calculation units in the target time period to obtain water quality indexes of each of the N predetermined risk levels.

[0008] According to an embodiment of the present invention, precipitation data includes one or more of monthly total, rainfall per session, maximum daily rainfall, longest rainy period, longest rainless period, maximum continuous rainfall, and number of rainy days with different rainfall intensity thresholds.

[0009] According to an embodiment of the present invention, the sponge project design data includes one or more of the runoff control rate, peak flow reduction rate, rainwater resource utilization rate, pollutant removal efficiency, permeable pavement coverage rate, and storage facility capacity.

[0010] According to an embodiment of the present invention, determining the risk level corresponding to each of the M time periods based on the hydrological data of the target urban area within the M time periods includes: calculating the mean and variance of the hydrological data based on the hydrological data of the target urban area within the M time periods; and determining the risk level corresponding to each of the M time periods based on the hydrological data, the mean and the variance.

[0011] According to an embodiment of the present invention, the N predetermined risk levels include no risk level, low risk level, lower risk level, medium risk level, higher risk level and high risk level.

[0012] According to an embodiment of the present invention, determining the risk level corresponding to each of the M time periods based on the hydrological data, the average value and the variance includes: The risk level of the time period within the range is determined to be no risk level, and the corresponding hydrological index is 0; the hydrological data is The risk level of the time period within the range is determined to be low risk level, and the corresponding hydrological index is 20%; the hydrological data is The risk level of the time period within the range is determined to be a lower risk level, and the corresponding hydrological index is 40%; the hydrological data is The risk level of the time period within the range is determined to be medium risk level, and the corresponding hydrological index is 60%; the hydrological data is The risk level of the time period within the range is determined to be a high risk level, and the corresponding hydrological index is 80%; the hydrological data is The risk level of the time period within the range is determined to be high risk, and the corresponding hydrological index is 100%; is the mean value of the hydrological data, S is the variance of the hydrological data, is the maximum value of the hydrological data.

[0013] According to an embodiment of the present invention, the water quality data includes one or more of dissolved oxygen, ammonia nitrogen, total phosphorus, and chemical oxygen demand.

[0014] According to an embodiment of the present invention, determining the resilience index of the water environment of the target urban area based on the water quality index and hydrological index of each of N predetermined risk levels includes: drawing a water quality-hydrological curve based on the water quality index and hydrological index of each of the N predetermined risk levels, wherein the water quality-hydrological curve is a curve showing that the water quality index changes with the hydrological index; and integrating the water quality-hydrological curve to obtain the resilience index of the water environment of the target urban area.

[0015] Another aspect of the present invention provides a device for determining the resilience index of an urban water environment, comprising: a first determination module, for determining the risk level corresponding to each of the M time periods based on the hydrological data of the target urban area within the M time periods, wherein the risk level corresponding to each time period is one of N predetermined risk levels, and the N predetermined risk levels correspond to N different hydrological indices according to the risk level value, and M and N are each independently integers greater than or equal to 1, and the hydrological data include at least one of precipitation data and sponge project design data; an acquisition module, for obtaining the water quality index of each of the N predetermined risk levels based on the water quality data of the target urban area within the M time periods, wherein the water quality data include the physical and chemical properties data of the water body in the target urban area, and the water quality index is used to characterize the degree of fluctuation of the water environment of the target urban area corresponding to each predetermined risk level; a second determination module, for determining the resilience index of the water environment of the target urban area based on the water quality index and hydrological index of each of the N predetermined risk levels.

[0016] Another aspect of the present invention provides an electronic device, comprising: one or more processors; and a memory for storing one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors implement the method described above.

[0017] Another aspect of the present invention provides a computer-readable storage medium storing computer-executable instructions, wherein the instructions are used to implement the above method when executed.

[0018] Another aspect of the present invention provides a computer program product, which includes computer executable instructions. When the instructions are executed, they are used to implement the method described above.

[0019] According to an embodiment of the present invention, at least one of precipitation data and sponge project design data (hydrological data) is selected as a factor (stress) affecting the water environment of a target urban area due to flood season pollution. Based on the hydrological data of the target urban area, a risk level corresponding to each time period is determined. The risk level corresponding to each time period is one of multiple predetermined risk levels. The multiple predetermined risk levels correspond to different hydrological indices depending on the risk level, thereby improving the practicality and operability of the calculation results. The physical and chemical property data of the water body in the target urban area (water quality data) is selected as a variable. Based on the water quality data of the target urban area, a water quality index (strain) for each of the multiple predetermined risk levels is obtained. The resilience index of the water environment in the target urban area is determined based on the water quality index and hydrological index for each of the multiple predetermined risk levels. The resilience index of the water environment determined by the method provided by the present invention is more accurate, practical, and operable, and has diverse application scenarios.

[0020] The method for determining the resilience index of the urban water environment provided by the embodiment of the present invention can accurately and quantitatively identify the resilience of the water environment of the target urban area. By comparing the resilience index under different hydrological data, it can identify the key factors that limit the target urban area's ability to cope with flood season pollution under the current urban ecological infrastructure, and provide guidance for optimization measures for urban construction. It is simple, easy to use, and highly applicable. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] The above and other objects, features and advantages of the present invention will become more apparent through the following description of the embodiments of the present invention with reference to the accompanying drawings, in which:

[0022] Figure 1 Schematically illustrates an exemplary system architecture of a method and apparatus for determining a resilience index of an urban water environment that can be applied according to an embodiment of the present invention;

[0023] Figure 2 A flowchart schematically illustrates a method for determining a resilience index of an urban water environment according to an embodiment of the present invention;

[0024] Figure 3 Schematically showing toughness evaluation results under different stress modes according to Example 1 of the present invention;

[0025] Figure 4 The schematic diagram shows the toughness improvement under different optimization conditions according to Example 1 of the present invention;

[0026] Figure 5 A block diagram schematically illustrates a device for determining a resilience index of an urban water environment according to an embodiment of the present invention;

[0027] Figure 6 A block diagram of an electronic device suitable for implementing a method for determining a resilience index of an urban water environment according to an embodiment of the present invention is schematically shown. DETAILED DESCRIPTION

[0028] Hereinafter, embodiments of the present invention will be described with reference to the accompanying drawings. However, it should be understood that these descriptions are exemplary only and are not intended to limit the scope of the present invention. In the following detailed description, for ease of explanation, many specific details are set forth to provide a comprehensive understanding of embodiments of the present invention. However, it is apparent that one or more embodiments may also be implemented without these specific details. In addition, in the following description, descriptions of known structures and technologies are omitted to avoid unnecessary confusion of the concept of the present invention.

[0029] The terms used herein are only for describing specific embodiments and are not intended to limit the present invention. The terms "comprise", "include", etc. used herein indicate the presence of the features, steps, operations and / or components, but do not exclude the presence or addition of one or more other features, steps, operations or components.

[0030] All terms used herein (including technical and scientific terms) have the meanings commonly understood by those skilled in the art unless otherwise defined. It should be noted that the terms used herein should be interpreted as having a meaning consistent with the context of this specification and should not be interpreted in an idealized or overly rigid manner.

[0031] When expressions such as "at least one of A, B, and C, etc." are used, they should generally be interpreted in accordance with the meaning commonly understood by those skilled in the art (for example, "a system having at least one of A, B, and C" should include but is not limited to a system having A alone, B alone, C alone, A and B, A and C, B and C, and / or A, B, C, etc.).

[0032] In the present invention, the resilience of the urban water environment may refer to the comprehensive ability of the urban water environment to respond to and recover under the pressure caused by uncertain events.

[0033] While the overall quality of urban water environments is showing a sustained improvement, flood season pollution is becoming increasingly prominent, becoming a key factor limiting further improvements. While sponge cities are widely recognized for their effectiveness in improving water environments, their resilience during flood season is relatively weak, preventing them from fully realizing their potential to mitigate flood season pollution. Therefore, there is an urgent need to calculate the resilience of urban water environments so that urban ecological infrastructure can be optimized based on this resilience level to address flood season pollution.

[0034] In the process of realizing the concept of the present invention, it was found that the time parameter can be simplified by replacing space with time, thereby reducing the problem of difficulty in determining the time parameter and increasing the diversity of application scenarios; by introducing a risk level classification method, the practicality and operability of the assessment results are improved; and by calculating the toughness index, comparative analysis between different stress modes is achieved, thereby enhancing the explanatory power of the calculation results.

[0035] Specifically, an embodiment of the present invention provides a method for determining the resilience index of an urban water environment, comprising the following steps: determining the risk level corresponding to each of the M time periods of a predetermined risk level based on the hydrological data of a target urban area within M time periods, wherein the risk level corresponding to each time period is one of N predetermined risk levels, and the predetermined risk levels N predetermined risk levels correspond to N different hydrological indices according to the risk level value, M and N are each independently integers greater than or equal to 1, and the predetermined risk level hydrological data include at least one of precipitation data and sponge project design data; obtaining the water quality index of each of the N predetermined risk levels of the predetermined risk level based on the water quality data of the target urban area of ​​the predetermined risk level within the M time periods of the predetermined risk level, wherein the predetermined risk level water quality data includes the physical and chemical property data of the water body of the target urban area of ​​the predetermined risk level, and the predetermined risk level water quality index is used to characterize the degree of fluctuation of the water environment of the target urban area of ​​the predetermined risk level corresponding to each predetermined risk level; determining the resilience index of the water environment of the target urban area of ​​the predetermined risk level based on the water quality index of each of the N predetermined risk levels of the predetermined risk level and the predetermined risk level hydrological index.

[0036] Figure 1 The following schematically illustrates an exemplary system architecture 100 to which a method and apparatus for determining a resilience index of an urban water environment according to an embodiment of the present invention may be applied. Figure 1 The examples shown are merely examples of system architectures to which the embodiments of the present invention may be applied, to help those skilled in the art understand the technical content of the present invention, but do not mean that the embodiments of the present invention cannot be used in other devices, systems, environments or scenarios.

[0037] like Figure 1 As shown, the system architecture 100 according to this embodiment may include a first terminal device 101, a second terminal device 102, a third terminal device 103, a network 104, and a server 105. The network 104 is used as a medium for providing a communication link between the first terminal device 101, the second terminal device 102, the third terminal device 103, and the server 105. The network 104 may include various connection types, such as wired and / or wireless communication links, etc.

[0038] A user may use a first terminal device 101, a second terminal device 102, or a third terminal device 103 to interact with a server 105 via a network 104 to receive or send messages, etc. Various communication client applications may be installed on the first terminal device 101, the second terminal device 102, or the third terminal device 103, such as shopping applications, web browser applications, search applications, instant messaging tools, email clients, and / or social platform software (for example only).

[0039] The first terminal device 101 , the second terminal device 102 , and the third terminal device 103 may be various electronic devices having display screens and supporting web browsing, including but not limited to smart phones, tablet computers, laptop computers, desktop computers, and the like.

[0040] The server 105 may be a server that provides various services, such as a background management server (for example only) that supports websites browsed by users using the first terminal device 101, the second terminal device 102, and the third terminal device 103. The background management server may analyze and process received data such as user requests, and feed back processing results (e.g., web pages, information, or data obtained or generated based on user requests) to the terminal devices.

[0041] It should be noted that the method for determining the resilience index of an urban water environment provided in the embodiment of the present invention can generally be executed by the server 105. Accordingly, the apparatus for determining the resilience index of an urban water environment provided in the embodiment of the present invention can generally be located in the server 105. The method for determining the resilience index of an urban water environment provided in the embodiment of the present invention can also be executed by a server or server cluster that is different from the server 105 and that is capable of communicating with the first terminal device 101, the second terminal device 102, the third terminal device 103, and / or the server 105. Accordingly, the apparatus for determining the resilience index of an urban water environment provided in the embodiment of the present invention can also be located in a server or server cluster that is different from the server 105 and that is capable of communicating with the first terminal device 101, the second terminal device 102, the third terminal device 103, and / or the server 105. Alternatively, the method for determining the resilience index of an urban water environment provided in the embodiment of the present invention can also be executed by the first terminal device 101, the second terminal device 102, or the third terminal device 103, or by another terminal device different from the first terminal device 101, the second terminal device 102, or the third terminal device 103. Correspondingly, the device for determining the resilience index of the urban water environment provided in the embodiment of the present invention can also be set in the first terminal device 101, the second terminal device 102 or the third terminal device 103, or in other terminal devices different from the first terminal device 101, the second terminal device 102 or the third terminal device 103.

[0042] For example, the hydrological data of the target urban area within M time periods and the water quality data of the target urban area within M time periods can be originally stored in any one of the first terminal device 101, the second terminal device 102, or the third terminal device 103 (for example, the first terminal device 101, but not limited thereto), or stored on an external storage device and imported into the first terminal device 101. Then, the first terminal device 101 can locally execute the method for determining the resilience index of the urban water environment provided in the embodiment of the present invention, or send the hydrological data of the target urban area within M time periods and the water quality data of the target urban area within M time periods to other terminal devices, servers, or server clusters, and the other terminal devices, servers, or server clusters that receive the hydrological data of the target urban area within M time periods and the water quality data of the target urban area within M time periods execute the method for determining the resilience index of the urban water environment provided in the embodiment of the present invention.

[0043] It should be understood that Figure 1 The number of terminal devices, networks and servers in the embodiment is merely illustrative. Any number of terminal devices, networks and servers may be provided as required.

[0044] Figure 2 The flowchart of the method for determining the resilience index of the urban water environment according to an embodiment of the present invention is schematically shown.

[0045] like Figure 2 As shown, the method includes operations S100 to S300.

[0046] In operation S100, based on the hydrological data of the target urban area in M ​​time periods, the risk level corresponding to each of the M time periods is determined, wherein the risk level corresponding to each time period is one of N predetermined risk levels, and the N predetermined risk levels correspond to N different hydrological indices according to the risk level values, M and N are each independently integers greater than or equal to 1, and the hydrological data includes at least one of precipitation data and sponge project design data.

[0047] In operation S200, based on the water quality data of the target urban area during M time periods, a water quality index for each of N predetermined risk levels is obtained, wherein the water quality data includes the physical and chemical properties of the water body in the target urban area, and the water quality index is used to characterize the degree of fluctuation of the water environment in the target urban area corresponding to each predetermined risk level.

[0048] In operation S300 , a resilience index of a water environment in a target urban area is determined based on the water quality index and the hydrological index of each of N predetermined risk levels.

[0049] According to an embodiment of the present invention, at least one of precipitation data and sponge project design data (hydrological data) is selected as a factor (stress) affecting the water environment of a target urban area due to flood season pollution. Based on the hydrological data of the target urban area, a risk level corresponding to each time period is determined. The risk level corresponding to each time period is one of multiple predetermined risk levels. The multiple predetermined risk levels correspond to different hydrological indices depending on the risk level, thereby improving the practicality and operability of the calculation results. Furthermore, the physical and chemical property data of the water body in the target urban area (water quality data) is selected as a variable. Based on the water quality data of the target urban area, a water quality index (strain) for each of the multiple predetermined risk levels is obtained. Based on the water quality index and hydrological index for each of the multiple predetermined risk levels, a resilience index for the water environment in the target urban area is determined. The method provided by the present invention can accurately and quantitatively identify the resilience of the water environment in the target urban area, has high practicality and operability, and is suitable for a variety of application scenarios.

[0050] According to an embodiment of the present invention, before operation S100, operation S050 may be further included. In operation S050, in response to receiving a request to determine a resilience index of the water environment of a target urban area, hydrological data and water quality data of the target urban area are obtained. The hydrological data of the target urban area includes hydrological data of the target urban area within M time periods, and the water quality data of the target urban area includes water quality data of the target urban area within M time periods. The hydrological data and / or water quality data of the target urban area may be stored in a database. The hydrological data and / or water quality data in the database may be divided according to time periods to facilitate subsequent processing of the hydrological data and / or water quality data.

[0051] According to an embodiment of the present invention, in operation S100, in the specific implementation process, illustratively, the M time periods can be 12 months, wherein each time period can be 1 month or 2 months, that is, M is 12 or 6; the M time periods can also be 6 months, wherein each time period can be 1 month, that is, M is 6; the M time periods can also be 24 months, wherein each time period can be 2 months, that is, M is 12.

[0052] According to an embodiment of the present invention, the target urban area may be an area for which the resilience index of the water environment needs to be determined. For example, the target urban area may be multiple cities, a city, or a part of a city, etc. The target urban area may not include or may include at least one sponge project.

[0053] According to an embodiment of the present invention, before operation S100, the relationship between the raw hydrological data and the water quality data can also be analyzed, including but not limited to correlation analysis, random forest analysis, interpretable machine learning, causal inference, stratified sampling, etc., to screen key influencing factors from the raw hydrological data and determine the hydrological data for the target urban area. By screening the hydrological data for the target urban area, the stress model setting is more precise, improving the accuracy of the resilience index.

[0054] According to an embodiment of the present invention, the hydrological data may be precipitation data, and may include one or more of the precipitation data. The hydrological data may also be sponge project design data, and may include one or more of the sponge project design data. The hydrological data may also include precipitation data and sponge project design data, and may include one or more of the precipitation data, and may include one or more of the sponge project design data. Exemplarily, the hydrological data of the target urban area may be:

[0055] .

[0056] Exemplarily, precipitation data may include one or more of the following: monthly total, rainfall per session, maximum daily rainfall, longest rainy period, longest rainless period, maximum continuous rainfall, and number of rainy days with different rainfall intensity thresholds. Among them, different rainfall intensity thresholds include but are not limited to rainfall of more than 2 mm, rainfall of more than 13.5 mm, rainfall of more than 22.5 mm, and rainfall of more than 33.5 mm. Specifically, the number of rainy days with different rainfall intensity thresholds include but are not limited to rainfall of more than 2 mm, rainfall of more than 13.5 mm, rainfall of more than 22.5 mm, and rainfall of more than 33.5 mm. Further, the number of rainy days with different rainfall intensity thresholds may be the number of rainy days with different rainfall intensity thresholds in each month. Sponge project design data may be data related to sponge project design, for example, it may include one or more of the following: runoff control rate, peak flow reduction rate, rainwater resource utilization rate, pollutant removal efficiency, permeable pavement coverage rate, and storage facility capacity. Table 1 shows some hydrological data and their definitions.

[0057] Table 1

[0058]

[0059] According to an embodiment of the present invention, considering the characteristics of rainfall during the flood season, precipitation data can be divided into two categories: short-term heavy rainfall data and long-term continuous rainfall data. Short-term heavy rainfall data can include SDII, R×1, R13.5, R22.5, R33.5, etc.; long-term continuous rainfall data can include R2, PRCPTOT, CWD, CDD, R×n, etc.

[0060] Furthermore, the hydrological data of the target urban area may include short-term heavy rainfall data, long-term continuous rainfall data, and sponge project design data. Stratified sampling can be used to screen key influencing factors in precipitation data, and one data point is randomly selected from each indicator category as the hydrological data of the target urban area. For example, the hydrological data of the target urban area can be:

[0061] .

[0062] According to an embodiment of the present invention, the magnitude of the hydrological index can represent the risk level value, and the magnitude of the risk level value can represent the level of risk. A predetermined risk level with a higher risk can have a higher hydrological index, while a predetermined risk level with a lower risk can have a lower hydrological index. The hydrological index can be any value, for example, any value between 0 and 100; the hydrological index can also be any value between 0 and 1 to facilitate analysis and comparison.

[0063] According to an embodiment of the present invention, in operation S100, in the specific implementation process, illustratively, the minimum and maximum values ​​of the hydrological data can be obtained based on the hydrological data of the target urban area within M time periods; the hydrological data can be equally divided into N hydrological data ranges based on the minimum and maximum values; and the risk level corresponding to each of the M time periods can be determined based on the N hydrological data ranges and the hydrological data of the target urban area within M time periods.

[0064] Another implementation manner is: operation S100 includes operations S110 and S120.

[0065] In operation S110 , the average value and variance of the hydrological data are calculated based on the hydrological data of the target urban area in M ​​time periods.

[0066] In operation S120 , the risk level corresponding to each of the M time periods is determined based on the hydrological data, the average value, and the variance.

[0067] According to an embodiment of the present invention, the average value of the hydrological data may be any one of an arithmetic mean, a geometric mean, a square mean, a weighted mean, etc. For example, the average value of the hydrological data is It can be the arithmetic mean and can be calculated according to formula (1). The variance S of the hydrological data can be calculated according to formula (2).

[0068] (1).

[0069] (2).

[0070] Among them, x krepresents the hydrological data value of the kth time period, and M represents the number of time periods.

[0071] According to an embodiment of the present invention, in operation S100, in the specific implementation process, illustratively, the N predetermined risk levels may also be 4 predetermined risk levels, namely, no risk level, low risk level, medium risk level and high risk level; the N predetermined risk levels may also be 4 predetermined risk levels, namely, low risk level, lower risk level, medium risk level and higher risk level.

[0072] In another implementation, the N predetermined risk levels may include 6 predetermined risk levels, namely no risk level, low risk level, lower risk level, medium risk level, higher risk level and high risk level.

[0073] Therefore, operation S120 includes operations S121 to S126.

[0074] In operation S121, the hydrological data is The risk level for time periods within this range is determined to be zero, and the corresponding hydrological index is 0. Values ​​within this range indicate that the hydrological data has no impact on the water environment or sponge projects in the target urban area, indicating that the water environment in the target urban area can operate normally or the sponge projects can function normally.

[0075] In operation S122, the hydrological data is The risk level for the time period within this range is determined to be low, with a corresponding hydrological index of 20%. Values ​​within this range indicate that the hydrological data has little impact on the water environment or sponge projects in the target urban area and is within normal fluctuations.

[0076] In operation S123, the hydrological data is The risk level for the time period within this range is determined to be low, with a corresponding hydrological index of 40%. Values ​​within this range indicate that the impact of the hydrological data on the water environment or sponge projects in the target urban area is slightly higher than normal, but still within controllable levels.

[0077] In operation S124, the hydrological data is The risk level for the time period within this range is determined to be medium, with a corresponding hydrological index of 60%. Values ​​within this range indicate that the hydrological data has an average impact on the water environment or sponge projects in the target urban area, requiring attention.

[0078] In operation S125, the hydrological data is stored in The risk level for time periods within this range is determined to be high, with a corresponding hydrological index of 80%. Values ​​within this range indicate that the impact of the hydrological data on the water environment or sponge projects in the target urban area is significantly higher than normal, and appropriate intervention measures are required.

[0079] In operation S126, the hydrological data is stored in The risk level for time periods within this range is determined to be high, with a corresponding hydrological index of 100%. Values ​​within this range indicate that the hydrological data has an extremely serious impact on the water environment or sponge projects in the target urban area, potentially leading to severe water quality deterioration or other problems, and that emergency measures must be taken immediately.

[0080] in, is the mean value of the hydrological data, S is the variance of the hydrological data, is the maximum value of the hydrological data.

[0081] According to an embodiment of the present invention, the water quality data includes data on the physical and chemical properties of water in the target urban area. Specifically, the water quality data may include data on the types and quantities of impurities in the water environment of the target urban area. For example, the water quality data may include one or more of dissolved oxygen, ammonia nitrogen, total phosphorus, and chemical oxygen demand.

[0082] According to an embodiment of the present invention, the time period corresponding to each predetermined risk level can be obtained according to operation S100; in operation S200, the water quality index corresponding to each predetermined risk level can be obtained based on the water quality data of the time period corresponding to each predetermined risk level.

[0083] According to an embodiment of the present invention, for a no-risk level, it can be assumed that the hydrological data has no impact on the water environment or sponge project in the target urban area. In this case, the water environment in the target urban area remains unchanged or the sponge project can fully function, and the water quality index can be set to 0. For a high-risk level, it can be assumed that the water environment in the target urban area has been severely damaged or the sponge project has deteriorated to the point where it cannot be restored by conventional means. Therefore, it can be considered as completely deformed, and the water quality index can be set to 1.

[0084] The water quality index for low risk level, lower risk level, medium risk level and higher risk level can be obtained by referring to the following method. In operation S200, for any i-th predetermined risk level, wherein, , including operations S211~S214.

[0085] In operation S211 , at least one target time period corresponding to an i-th predetermined risk level among the M time periods is determined.

[0086] In operation S212 , a water quality score for the target time period is obtained based on the water quality data of the target city area within the target time period, wherein water quality data in different concentration ranges correspond to different water quality scores.

[0087] In operation S213 , a maximum water quality score of the M time periods is obtained based on the water quality data of the target urban area in the M time periods.

[0088] In operation S214 , a water quality index of the i-th predetermined risk level is calculated based on the water quality score of the target time period and the maximum water quality score of the M time periods to obtain water quality indexes of the N predetermined risk levels.

[0089] According to an embodiment of the present invention, in operation S212, water quality data may be collected through online monitoring, laboratory analysis, portable instruments, remote sensing monitoring, etc. The water quality data may include but is not limited to dissolved oxygen (DO), ammonia nitrogen ( ), total phosphorus (TP), chemical oxygen demand and other key indicators. For example, chemical oxygen demand can be expressed as permanganate index ( ) can also be characterized by the dichromate index ( ) for characterization. Collected data can be preprocessed, including but not limited to removing outliers, filling in missing values, and standardizing, to ensure data quality and consistency. Water quality scores and weights can be determined using a unified, staged threshold based on literature analysis methods, for example. See Table 2 for details, which schematically illustrates typical water quality scores and weights.

[0090] Table 2

[0091]

[0092] Water quality scores can also be obtained by normalizing them according to national standards. The calculation method refers to formula (3).

[0093] (3).

[0094] Among them, C j is the water quality score of water quality data j, t j is the actual measured value of water quality data j, t min,j and t max,j are the minimum and maximum allowed values ​​of water quality data j in M ​​time periods.

[0095] According to an embodiment of the present invention, the weight of each water quality data can be determined according to the importance of the indicator and the degree of impact on water quality, including but not limited to expert scoring method, hierarchical analysis method or other multi-criteria decision-making methods.

[0096] According to an embodiment of the present invention, in operation S212, the water quality score and the maximum water quality score for each predetermined risk level may be calculated with reference to formula (4).

[0097] (4).

[0098] in, is the water quality score of the i-th predetermined risk level, C j is the water quality score of water quality data j; P j is the weight corresponding to water quality data j.

[0099] The change in water quality score can be calculated by referring to formula (5) and regarded as the water quality index of the urban water environment as the strain:

[0100] (5).

[0101] Among them, WQI max is the maximum water quality score within M time periods.

[0102] According to an embodiment of the present invention, the target urban area includes multiple calculation units. The multiple calculation units can be determined based on the geographical information of the target urban area and the regional drainage plan. For example, the target urban area can be divided into multiple calculation units based on terrain characteristics, population density, drainage paths, etc. to ensure internal consistency and external differences of each calculation unit. Each calculation unit can have a clear boundary. Each calculation unit can contain no or at least one sponge project to facilitate subsequent analysis.

[0103] As another embodiment, in operation S200, for any i-th predetermined risk level, , and may also include operations S221~S225.

[0104] In operation S221 , at least one target time period corresponding to an i-th predetermined risk level among the M time periods is determined.

[0105] In operation S222 , a water quality score of each calculation unit within the target time period is obtained based on the water quality data of each calculation unit within the target time period, wherein water quality data in different concentration ranges correspond to different water quality scores.

[0106] In operation S223 , a maximum water quality score of each calculation unit in the M time periods is obtained based on the water quality data of each calculation unit in the M time periods.

[0107] In operation S224, the water quality index of each calculation unit in the target time period is calculated according to the water quality score of each calculation unit in the target time period and the maximum water quality score of each calculation unit in the M time periods, thereby obtaining the water quality index of each of the multiple calculation units in the target time period.

[0108] In operation S225 , the water quality index of the i-th predetermined risk level is calculated according to the respective water quality indices of the plurality of calculation units within the target time period to obtain respective water quality indices of N predetermined risk levels.

[0109] According to an embodiment of the present invention, in operation S300, in the specific implementation process, illustratively, the resilience index of each predetermined risk level can be calculated separately to obtain N resilience indices; and then the N resilience indices are weighted and summed to obtain the resilience index of the water environment of the target urban area.

[0110] Another implementation manner is: operation S300 includes S310 and S320.

[0111] In operation S310 , a water quality-hydrology curve is drawn according to the water quality index and the hydrological index of each of the N predetermined risk levels, wherein the water quality-hydrology curve is a curve showing changes in the water quality index as the hydrological index changes.

[0112] In operation S320 , the drawn water quality-hydrology curve is integrated to obtain a resilience index of the water environment of the target urban area.

[0113] According to an embodiment of the present invention, the water quality-hydrology curve may be plotted by integrating the water quality-hydrology curve or the area under the curve (AUC) of each performance metric may be calculated using the trapezoidal rule, with reference to formula (6).

[0114] (6).

[0115] Where a and b represent the upper and lower limits of the hydrological index; N is the number of predetermined risk levels; Indicates the water quality index when the hydrological index is x; The hydrological index is When , the corresponding water quality index; The hydrological index is When , the corresponding water quality index, x and n are variables.

[0116] According to an embodiment of the present invention, a larger resilience index indicates a lower resilience of the target city's water environment; a lower resilience index indicates a higher resilience of the target city's water environment. To further enhance the explanatory power of the resilience index and enable comparative analysis across different models, the resilience index can be normalized to obtain a normalized resilience index (Res). A larger normalized resilience index indicates a higher resilience of the target city's water environment. Specifically, the normalization process can refer to Formula (7).

[0117] (7).

[0118] According to an embodiment of the present invention, the hydrological data includes multiple sets of hydrological sub-data, each of which includes different hydrological data. Based on the multiple sets of hydrological sub-data, the above-mentioned method for determining the resilience index of the urban water environment is used to obtain the resilience index of the water environment of multiple target urban areas. The method for determining the resilience index of the urban water environment provided by the embodiment of the present invention can quantitatively identify the resilience of the water environment of the target urban area. By comparing the resilience index under different hydrological data, the key factors that limit the target urban area's ability to cope with flood season pollution can be identified, providing guidance for optimizing urban construction measures.

[0119] According to embodiments of the present invention, the hydrological data for a target urban area may include measured hydrological data for the target urban area. The resilience index calculated based on the measured hydrological data for the target urban area can characterize the resilience of the target urban area's water environment under different pressure conditions (hydrological data). Based on the calculated resilience level of the target urban area's water environment, urban construction can be optimized to address flood season pollution.

[0120] According to an embodiment of the present invention, the hydrological data of the target urban area may also include predicted or simulated hydrological data of the target urban area. Optimization measures for different failure modes can be set, including but not limited to increasing the capacity of the reservoir, improving the sewer system, implementing an intelligent rainwater management system, increasing the permeable pavement area, optimizing the green space design, etc., and corresponding optimization scenarios can be constructed; the performance of the urban water environment under different urban construction optimization scenarios can be simulated, and the method for determining the resilience index of the urban water environment provided by the embodiment of the present invention can be used to calculate the change in the resilience index before and after the implementation of the optimization measures, determine the effect of the optimization measures on the resilience of the water environment, and thereby evaluate the effectiveness of the optimization measures, and determine the optimal combination of optimization measures, thereby helping to optimize the anti-pollution resilience of the target urban area or sponge project at the engineering design level, and having the characteristics of being simple, easy to use, and highly applicable. The advantage of the embodiment of the present invention is that it can provide a more comprehensive and practical calculation and optimization method, enhance the risk resistance and recovery capacity of the water environment system, and improve the actual application effect of the method.

[0121] According to an embodiment of the present invention, by combining the stress characteristics of the target urban area (which may include sponge projects), the time parameter is simplified into one of the independent stress modes. This method then determines an assessment method for the resilience of the target urban area to flood season pollution control under different regional precipitation conditions, and proposes a solution for improving the resilience of the target urban area to flood season pollution control. Using precipitation data and sponge project design data, key factors limiting the target urban area's ability to cope with flood season pollution can be identified, and the effect of improving these factors on water environment resilience can be evaluated and simulated, thereby helping to improve the resilience of the target urban area at the engineering design level. This method has the advantages of being simple to operate, comprehensively considering regional climate and urban construction characteristics, and is suitable for large-scale spatiotemporal analysis.

[0122] According to an embodiment of the present invention, the sponge project design data to be optimized can be determined based on the resilience index of the water environment of the target urban area; based on the sponge project design data to be optimized, an optimized flood season pollution plan can be determined, and the optimized flood season pollution plan is a plan to enhance the resilience of the target urban area in responding to flood season pollution prevention and control; and the optimized flood season pollution plan is executed to enhance the resilience index of the water environment of the target urban area. Optionally, based on the sponge project design data to be optimized, optimization measures can be set for different hydrological data to determine an optimized flood season pollution plan. The optimized flood season pollution plan includes but is not limited to increasing the capacity of the reservoir, improving the sewer system, implementing an intelligent rainwater management system, increasing the permeable pavement area, optimizing the green space design, etc.

[0123] The following specific embodiments are given to illustrate the technical solution of the present invention in detail. It should be noted that the following specific embodiments are only for illustration and are not intended to limit the present invention.

[0124] Example 1

[0125] This example uses a typical plain river network area as the test site. Based on online water quality observation data, 248 rivers are selected. The urban water environment is used as the receiving water body to analyze the background resilience of the urban water environment and the level of resilience improvement under various typical optimization scenarios. The proposed methodology is experimentally verified.

[0126] (1) Based on factors such as topographic features, drainage paths, and population density, and in combination with geographic information system technology and regional drainage planning, each assessment unit is ensured to be internally consistent and externally diverse. The study area in this example is ultimately subdivided into 41 assessment units, each containing one or more sponge projects for subsequent analysis.

[0127] (2) Collect and record meteorological and hydrological data such as rainfall. In this embodiment, precipitation data (monthly total amount, rainfall per session, maximum daily rainfall, longest rainy period, longest rainless period, maximum continuous rainfall, number of days with rainfall above 2 mm, number of days with rainfall above 13.5 mm, number of days with rainfall above 22.5 mm, and number of days with rainfall above 33.5 mm) and sponge project design data (runoff control rate) are selected as limiting factors for the sponge project to cope with flood season pollution. See Table 1 for details.

[0128] (3) Analyze the relationship between influencing factors and strain. In this embodiment, stratified sampling is used to screen key influencing factors. Considering the characteristics of rainfall during the flood season, the precipitation index is divided into two categories: short-term heavy rainfall and long-term continuous rainfall. At the same time, considering the design parameters of the sponge project, there are three types of stress.

[0129] Short-term heavy rainfall: SDII, R×1, R13.5, R22.5, R33.5, etc.

[0130] Long-term continuous rainfall: including R2, PRCPTOT, CWD, CDD, R×n, etc.

[0131] Sponge project design parameters: Runoff control, etc.

[0132] Finally, one indicator is randomly selected from each category as stress, which are:

[0133] .

[0134] (4) Select one of the various stresses that may affect the urban water environment for detailed analysis. In this example, the stress mode selected includes CWD and R13.5, as well as key indicators such as Runoff control. Based on historical data, the average value of the key indicators under the selected stress mode is calculated according to formulas (1) and (2): and standard deviation S.

[0135] According to the calculated mean and standard deviation, the impact of stress is divided into 6 levels.

[0136] No risk level: Values ​​within this range indicate that the stress has no effect on the sponge project, and are in an ideal state where the sponge project can function normally, recorded as stress = 0%.

[0137] Low risk level: The value within this range indicates that the stress has little impact on the sponge project and is within the normal fluctuation range, which is recorded as stress = 20%.

[0138] Lower risk level: A value within this range indicates that the stress has a slightly higher impact on the sponge project than normal, but is still within a controllable range, recorded as stress = 40%.

[0139] Medium risk level: Values ​​within this range indicate that the stress impact on the urban water environment has reached the average level and requires attention, which is recorded as stress = 60%.

[0140] Higher risk level: Values ​​within this range indicate that the impact of stress on the sponge project is significantly higher than normal, and appropriate intervention measures are required, recorded as stress = 80%.

[0141] High risk level: Values ​​within this range indicate that the stress has an extremely serious impact on the sponge project, which may cause serious water quality deterioration or other problems, and emergency measures must be taken immediately. This is recorded as stress = 100%.

[0142] (5) Within each assessment unit, ensure that water quality monitoring data is collected for at least one year before and after the sponge project is put into use. Based on the online monitoring water quality data, the water quality score for each time period is calculated by referring to the above formula (4) and Table 2. The degree of change is calculated according to the above formula (5) to serve as the water quality index for each time period, namely the strain, to evaluate the resilience index of the sponge project. Finally, the strain is classified by plot and the topological relationship between the strain and the target sponge project is established.

[0143] The strain calculation is divided into 6 levels. The strain of levels 2-5 is calculated according to the above method. At the same time, it is assumed that the sponge project under the stress of level 1 is not affected. At this time, the sponge project can fully exert its effectiveness, so the strain should be 0. At level 6, it is assumed that the sponge project has deteriorated to the point where it cannot be restored by conventional means. Therefore, it is considered to be fully deformed, and the strain is 1. In the absence of specific improvement measures, the resilience background index of the urban water environment under different stress conditions is calculated. In this embodiment, the upper and lower quartiles are used to show the uncertainty of the results to better express the fluctuation range and confidence level of the data. Based on stress and strain, a continuous strain-stress (f(x)-x) curve is constructed, and the area under the curve of each performance metric is calculated using the trapezoidal rule according to formula (6).

[0144] To further reflect the effect of different measures on improving resilience, the normalized value Res is used with reference to formula (7). A larger index indicates higher resilience.

[0145] First, calculate Res for the three cases. See the results for details. Figure 3 , Figure 3 The diagram schematically illustrates the toughness evaluation results under different stress modes according to Example 1 of the present invention. (a) shows the toughness evaluation result under the R13.5 stress mode, (b) shows the toughness evaluation result under the CWD stress mode, and (c) shows the toughness evaluation result under the Runoff control stress mode. max-min represents the maximum value minus the minimum value, and mean represents the average value.

[0146] (6) According to the design data of the sponge project to be optimized, set optimization measures for different stresses and determine the optimization plan for flood season pollution. The optimization plan for flood season pollution includes but is not limited to increasing the capacity of water storage tanks, improving sewer systems, implementing intelligent rainwater management systems, increasing permeable pavement areas, optimizing green space design, etc., and constructing corresponding optimization scenarios; stress is graded from low to high according to the degree of its impact on the urban water environment. For example, light short-term heavy rainfall is defined as first-level stress, while long-term continuous heavy rainfall may be defined as a higher level of stress; for each level of stress, design and gradually implement corresponding optimization measures; after each step of optimization measures is implemented, recalculate the strain. Strain reflects the degree of impact of the optimization measures on the urban water environment. Ideally, through effective optimization measures, the deformation value should be close to zero, indicating that the water quality index remains stable or improves; when the strain is 0 or reaches the expected optimal state, calculate the urban water environment resilience index under the stress.

[0147] Scenario 1: Engineering measures for CWD.

[0148] Step 1: Define a series of hypothetical engineering measures, such as increasing reservoir capacity, improving sewer systems, or implementing smart stormwater management systems, to alleviate pressure during CWD.

[0149] Step 2: Simulate the system's performance during CWD after implementing each measure, paying particular attention to whether the system can maintain an effective state (i.e., strain = 0) at different CWD lengths.

[0150] Step 3: Analyze and compare the efficiency of these measures in improving resilience, find the optimal combination of engineering measures, and under what CWD conditions these measures can most effectively improve resilience.

[0151] Scenario 2: Measures targeting R13.5.

[0152] Step 1: Similarly, for days with precipitation greater than 13.5 mm, design and hypothesize a series of strategies, such as increasing the permeable paving area and optimizing the green space design to enhance rainwater absorption capacity.

[0153] Step 2: Simulate the impact of these measures on system resilience, especially the system performance when rainfall exceeds a threshold, to assess under what criteria they can effectively improve resilience.

[0154] Scenario 3: Sponge city maintenance and upgrade.

[0155] Step 1: Assume a maintenance and upgrade strategy for sponge city facilities, including regular inspections, cleaning, replacement of aging components, and sponge transformation of new areas.

[0156] Step 2: Analyze how these maintenance and upgrade measures affect resilience based on different runoff control rates (e.g., 50%, 70%, 90%, etc.). Assess the system's ability to respond to various weather events at different control rates.

[0157] By simulating the performance of the urban water environment under different optimization scenarios and calculating the changes in Res before and after the implementation of the optimization measures, the effectiveness of the measures can be evaluated and the optimal combination of optimization solutions can be determined. After making scenario assumptions, the resilience improvement status under each scenario can be obtained. Figure 4 , Figure 4 The diagram schematically shows the toughness improvement status under different scenario optimization conditions according to Example 1 of the present invention, wherein (a) is the toughness improvement status under the optimization conditions of scenario 2, (b) is the toughness improvement status under the optimization conditions of scenario 1, and (c) is the toughness improvement status under the optimization conditions of scenario 3.

[0158] Figure 4 The Res in (a) shows a convex upward trend, indicating that by considering short-term moderate-intensity rainfall in the design, the Res in the study area can be effectively improved, effectively enhancing the local urban resilience. Technology for coping with short-term moderate-intensity rainfall (primarily gray infrastructure).

[0159] 1) Enhance rainwater infiltration facilities: Incorporate permeable pavement, bioretention ponds, rain gardens, and other facilities into urban design. These facilities can quickly absorb and store rainwater, reduce surface runoff, and prevent waterlogging.

[0160] 2) Rapid response drainage system: Upgrade the existing drainage system and add temporary water storage tanks or regulating tanks to quickly drain excess rainwater generated by moderate-intensity rainfall in a short period of time.

[0161] Figure 4The Res in (b) shows a concave upward trend, indicating that long-term continuous rainfall needs to be considered in the subsequent sponge city design to effectively improve Res and address the issue of sponge city failure in this region. Technologies for coping with long-term continuous rainfall (primarily green and blue facilities).

[0162] 1) Enhance underground water storage capacity: Design large underground water storage tanks and deep infiltration facilities to cope with prolonged rainfall and ensure that rainwater has sufficient space to be stored without causing ground waterlogging.

[0163] 2) Green roofs and vertical greening: Promote green roofs and wall greening to increase urban greening coverage, prolong the residence time of rainwater on the urban surface, gradually release it into the ground or evaporate, and reduce the pressure on the drainage system during continuous rainfall.

[0164] 3) Sponge system optimization: Optimize the sponge city design to ensure that each sponge body (such as parks, roads, communities, etc.) can be effectively connected to form a networked rainwater management system and improve the overall storage capacity of the system.

[0165] Figure 4 The Res in (c) shows a concave increase, which may indicate that sponge city construction with high runoff control rates has a greater effect on improving the city's Res. In the future, it will be necessary to strengthen plots with high runoff control rates to significantly improve the resilience of the region. Application of high runoff control rate technology.

[0166] 1) Application of high-strength permeable materials: In high-runoff areas such as urban roads and squares, new materials with high permeability are used for paving to quickly absorb and infiltrate rainwater.

[0167] 2) Ecological ditch and wetland systems: Construct or optimize ecological ditch and wetland systems in cities. These natural systems have high runoff control capacity and can effectively handle large amounts of stormwater while providing ecosystem services.

[0168] 3) Smart sponge city technology: Leveraging technologies such as the Internet of Things and big data, the runoff control effect of sponge facilities is monitored in real time. The layout and management strategies of sponge facilities are dynamically adjusted based on actual stormwater management conditions to ensure the sustainability and effectiveness of high runoff control rates.

[0169] Figure 5 A block diagram of a device for determining a resilience index of an urban water environment according to an embodiment of the present invention is schematically shown.

[0170] like Figure 5 As shown, the apparatus 500 for determining the resilience index of an urban water environment includes a first determining module 510 , an obtaining module 520 , and a second determining module 530 .

[0171] The first determination module 510 is used to determine the risk level corresponding to each of the M time periods based on the hydrological data of the target urban area within the M time periods, wherein the risk level corresponding to each time period is one of N predetermined risk levels, and the N predetermined risk levels correspond to N different hydrological indices according to the risk level values, M and N are each independently integers greater than or equal to 1, and the hydrological data includes at least one of precipitation data and sponge project design data.

[0172] Acquisition module 520 is used to obtain water quality indexes for each of N predetermined risk levels based on water quality data of the target urban area during M time periods, wherein the water quality data includes physical and chemical property data of water bodies in the target urban area, and the water quality index is used to characterize the degree of fluctuation of the water environment in the target urban area corresponding to each predetermined risk level.

[0173] The second determination module 530 is configured to determine the resilience index of the water environment of the target urban area according to the water quality index and the hydrological index of each of the N predetermined risk levels.

[0174] According to an embodiment of the present invention, the first determination module 510 includes a first calculation submodule and a first determination submodule. The first calculation submodule is configured to calculate the mean and variance of the hydrological data based on the hydrological data of the target urban area within M time periods; and the first determination submodule is configured to determine the risk level corresponding to each of the M time periods based on the hydrological data, the mean, and the variance.

[0175] According to an embodiment of the present invention, the N predetermined risk levels include no risk level, low risk level, lower risk level, medium risk level, higher risk level and high risk level.

[0176] According to an embodiment of the present invention, the first determining submodule includes a first determining unit, a second determining unit, a third determining unit, a fourth determining unit, a fifth determining unit and a sixth determining unit. The first determining unit is used to determine the hydrological data in The risk level of the time period within the range is determined as no risk level, and the corresponding hydrological index is 0; the second determination unit is used to determine the hydrological data in The risk level of the time period within the range is determined to be low risk level, and the corresponding hydrological index is 20%; the third determination unit is used to convert the hydrological data into The risk level of the time period within the range is determined to be a lower risk level, and the corresponding hydrological index is 40%; the fourth determination unit is used to convert the hydrological data into The risk level of the time period within the range is determined to be medium risk level, and the corresponding hydrological index is 60%; the fifth determination unit is used to convert the hydrological data into The risk level of the time period within the range is determined to be a high risk level, and the corresponding hydrological index is 80%; the sixth determination unit is used to convert the hydrological data into The risk level of the time period within the range is determined to be high risk, and the corresponding hydrological index is 100%; is the mean value of the hydrological data, S is the variance of the hydrological data, is the maximum value of the hydrological data.

[0177] According to an embodiment of the present invention, the obtaining module 520 includes a second determining submodule, a first obtaining submodule, a second obtaining submodule, and a second calculating submodule. The second determining submodule is configured to determine at least one target time period corresponding to the i-th predetermined risk level in the M time periods, wherein ; The first obtaining submodule is used to obtain the water quality score of the target time period based on the water quality data of the target urban area within the target time period, wherein water quality data in different concentration ranges correspond to different water quality scores; the second obtaining submodule is used to obtain the maximum water quality score of M time periods based on the water quality data of the target urban area within M time periods; the second calculating submodule is used to calculate the water quality index of the i-th predetermined risk level based on the water quality score of the target time period and the maximum water quality score of the M time periods, so as to obtain the water quality index of each of the N predetermined risk levels.

[0178] According to an embodiment of the present invention, the target city area includes a plurality of computing units.

[0179] According to an embodiment of the present invention, the obtaining module 520 includes a third determining submodule, a third obtaining submodule, a fourth obtaining submodule, a third calculating submodule, and a fourth calculating submodule. The third determining submodule is configured to determine at least one target time period corresponding to the i-th predetermined risk level in the M time periods, wherein: ; The third obtaining submodule is used to obtain the water quality score of each calculation unit in the target time period based on the water quality data of each calculation unit in the target time period, wherein water quality data in different concentration ranges correspond to different water quality scores; the fourth obtaining submodule is used to obtain the maximum water quality score of each calculation unit in M ​​time periods based on the water quality data of each calculation unit in M ​​time periods; the third calculating submodule is used to calculate the water quality index of each calculation unit in the target time period based on the water quality score of each calculation unit in the target time period and the maximum water quality score of each calculation unit in M ​​time periods, and obtain the water quality index of each of the multiple calculation units in the target time period; the fourth calculating submodule is used to calculate the water quality index of the i-th predetermined risk level based on the water quality index of each of the multiple calculation units in the target time period, so as to obtain the water quality index of each of the N predetermined risk levels.

[0180] Any number of the modules, submodules, units, and subunits according to embodiments of the present invention, or at least part of the functionality of any number of these units, can be implemented in a single module. Any one or more of the modules, submodules, units, and subunits according to embodiments of the present invention can be split into multiple modules for implementation. Any one or more of the modules, submodules, units, and subunits according to embodiments of the present invention can be at least partially implemented as a hardware circuit, such as a field programmable gate array (FPGA), a programmable logic array (PLA), a system on a chip, a system on a substrate, a system on a package, an application-specific integrated circuit (ASIC), or can be implemented in hardware or firmware using any other reasonable method of circuit integration or packaging, or can be implemented in any one of the three implementation methods of software, hardware, and firmware, or any appropriate combination of any of these. Alternatively, one or more of the modules, submodules, units, and subunits according to embodiments of the present invention can be at least partially implemented as a computer program module that, when executed, can perform the corresponding functionality.

[0181] For example, any multiple of the first determination module 510, the acquisition module 520, and the second determination module 530 may be combined and implemented in a single module / unit / sub-unit, or any one of these modules / units / sub-units may be split into multiple modules / units / sub-units. Alternatively, at least part of the functionality of one or more of these modules / units / sub-units may be combined with at least part of the functionality of other modules / units / sub-units and implemented in a single module / unit / sub-unit. According to an embodiment of the present invention, at least one of the first determination module 510, the acquisition module 520, and the second determination module 530 may be at least partially implemented as a hardware circuit, such as a field programmable gate array (FPGA), a programmable logic array (PLA), a system on a chip, a system on a substrate, a system on a package, an application-specific integrated circuit (ASIC), or may be implemented in hardware or firmware through any other reasonable means of circuit integration or packaging, or may be implemented in any one of software, hardware, and firmware, or any appropriate combination thereof. Alternatively, at least one of the first determination module 510 , the obtaining module 520 , and the second determination module 530 may be at least partially implemented as a computer program module, and when the computer program module is executed, the corresponding function may be executed.

[0182] It should be noted that the data processing system part in the embodiment of the present invention corresponds to the data processing method part in the embodiment of the present invention. The description of the data processing system part specifically refers to the data processing method part and will not be repeated here.

[0183] Figure 6A block diagram of an electronic device suitable for implementing a method for determining a resilience index of an urban water environment according to an embodiment of the present invention is schematically shown. Figure 6 The electronic device shown is only an example and should not limit the functions and scope of use of the embodiments of the present invention.

[0184] like Figure 6 As shown, an electronic device 600 according to an embodiment of the present invention includes a processor 601, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 602 or a program loaded from a storage unit 608 into a random access memory (RAM) 603. The processor 601 may include, for example, a general-purpose microprocessor (e.g., a CPU), an instruction set processor and / or a related chipset and / or a special-purpose microprocessor (e.g., an application-specific integrated circuit (ASIC)), etc. The processor 601 may also include onboard memory for caching purposes. The processor 601 may include a single processing unit or multiple processing units for performing different actions of the method flow according to an embodiment of the present invention.

[0185] Various programs and data required for the operation of the electronic device 600 are stored in the RAM 603. The processor 601, ROM 602, and RAM 603 are connected to each other via a bus 604. The processor 601 executes the programs in the ROM 602 and / or RAM 603 to perform various operations according to the method flow of the embodiment of the present invention. It should be noted that the programs may also be stored in one or more memories other than the ROM 602 and RAM 603. The processor 601 may also execute the programs stored in the one or more memories to perform various operations according to the method flow of the embodiment of the present invention.

[0186] According to an embodiment of the present invention, electronic device 600 may further include an input / output (I / O) interface 605, which is also connected to bus 604. Electronic device 600 may also include one or more of the following components connected to I / O interface 605: an input section 606 including a keyboard, mouse, etc.; an output section 607 including devices such as a cathode ray tube (CRT), liquid crystal display (LCD), and speakers; a storage section 608 including a hard disk; and a communication section 609 including a network interface card such as a LAN card or modem. Communication section 609 performs communication processing via a network such as the Internet. A drive 610 is also connected to I / O interface 605 as needed. Removable media 611, such as a magnetic disk, optical disk, magneto-optical disk, semiconductor memory, etc., is installed in drive 610 as needed, so that computer programs read from the removable media can be installed into storage section 608 as needed.

[0187] According to an embodiment of the present invention, the method flow according to an embodiment of the present invention can be implemented as a computer software program. For example, an embodiment of the present invention includes a computer program product, which includes a computer program carried on a computer-readable storage medium, and the computer program includes a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from the network through the communication part 609, and / or installed from the removable medium 611. When the computer program is executed by the processor 601, the above-mentioned functions defined in the system of the embodiment of the present invention are executed. According to an embodiment of the present invention, the system, device, apparatus, module, unit, etc. described above can be implemented by a computer program module.

[0188] The present invention also provides a computer-readable storage medium, which may be included in the device / apparatus / system described in the above embodiments, or may exist independently and not incorporated into the device / apparatus / system. The computer-readable storage medium carries one or more programs, which, when executed, implement the method according to the embodiments of the present invention.

[0189] According to embodiments of the present invention, a computer-readable storage medium may be a non-volatile computer-readable storage medium. Examples include, but are not limited to, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In the present invention, a computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.

[0190] For example, according to an embodiment of the present invention, the computer-readable storage medium may include the ROM 602 and / or the RAM 603 described above and / or one or more memories other than the ROM 602 and the RAM 603 .

[0191] An embodiment of the present invention also includes a computer program product, which includes a computer program, which contains program code for executing the method provided by the embodiment of the present invention. When the computer program product is run on an electronic device, the program code is used to enable the electronic device to implement the method for determining the resilience index of the urban water environment provided by the embodiment of the present invention.

[0192] When the computer program is executed by the processor 601, the above functions defined in the system / device of the embodiment of the present invention are performed. According to the embodiment of the present invention, the above-described systems, devices, modules, units, etc. can be implemented by computer program modules.

[0193] In one embodiment, the computer program may be stored on a tangible storage medium such as an optical storage device or a magnetic storage device. In another embodiment, the computer program may be transmitted and distributed in the form of a signal on a network medium, downloaded and installed via the communication portion 609, and / or installed from a removable medium 611. The program code contained in the computer program may be transmitted using any appropriate network medium, including but not limited to wireless, wired, or any suitable combination thereof.

[0194] According to an embodiment of the present invention, the program code for executing the computer program provided by the embodiment of the present invention can be written in any combination of one or more programming languages. Specifically, these computer programs can be implemented using high-level procedural and / or object-oriented programming languages, and / or assembly / machine languages. Programming languages ​​include, but are not limited to, languages ​​such as Java, C++, Python, "C" or similar programming languages. The program code can be executed entirely on the user computing device, partially on the user device, partially on a remote computing device, or entirely on a remote computing device or server. In the case of a remote computing device, the remote computing device can be connected to the user computing device through any type of network, including a local area network (LAN) or a wide area network (WAN), or can be connected to an external computing device (for example, using an Internet service provider to connect via the Internet).

[0195] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architectures, functions, and operations of the systems, methods, and computer program products according to various embodiments of the present invention. In this regard, each box in the flowchart or block diagram may represent a module, program segment, or portion of code, which contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the boxes may occur in an order different from that marked in the accompanying drawings. For example, two boxes shown in succession may actually be executed substantially in parallel, or they may sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram or flowchart, as well as the combination of boxes in the block diagram or flowchart, may be implemented using a dedicated hardware-based system that performs the specified function or operation, or may be implemented using a combination of dedicated hardware and computer instructions. It will be understood by those skilled in the art that the features described in the various embodiments of the present invention may be combined and / or coupled in various ways, even if such combinations or couplings are not explicitly described in the present invention. In particular, the features described in the various embodiments of the present invention may be combined and / or coupled in various ways without departing from the spirit and teachings of the present invention. All such combinations and / or combinations fall within the scope of the present invention.

[0196] The above describes embodiments of the present invention. However, these embodiments are for illustrative purposes only and are not intended to limit the scope of the present invention. Although each embodiment has been described separately above, this does not mean that the measures in each embodiment cannot be advantageously used in combination. Without departing from the scope of the present invention, those skilled in the art may make various substitutions and modifications, which should all fall within the scope of the present invention.

Claims

1. A method for determining the resilience index of an urban water environment, characterized in that: The following steps are involved: Determine, based on hydrological data of the target urban area within M time periods, a risk level corresponding to each of the M time periods, wherein the risk level corresponding to each time period is one of N predetermined risk levels, and the N predetermined risk levels correspond to N different hydrological indices according to risk level values, where M and N are each independently integers greater than or equal to 1, and the hydrological data includes at least one of precipitation data and sponge project design data; Obtaining a water quality index for each of the N predetermined risk levels based on water quality data of the target urban area during the M time periods, wherein the water quality data includes physical and chemical property data of water in the target urban area, and the water quality index is used to characterize the degree of fluctuation of the water environment in the target urban area corresponding to each predetermined risk level; determining a resilience index of the water environment of the target urban area based on the water quality index and the hydrological index of each of the N predetermined risk levels; The method of obtaining the water quality index of each of N predetermined risk levels based on the water quality data of the target urban area in M ​​time periods includes performing the following operations for any i-th predetermined risk level, wherein: : Determining at least one target time period corresponding to an i-th predetermined risk level among the M time periods; Based on the water quality data of the target city area during the target time period, the water quality score of the target time period is obtained, where water quality data in different concentration ranges correspond to different water quality scores; Obtaining a maximum water quality score for the M time periods based on the water quality data of the target urban area during the M time periods; The water quality index of the i-th predetermined risk level is calculated according to the water quality score of the target time period and the maximum water quality score of the M time periods to obtain the water quality index of each of the N predetermined risk levels.

2. The method for determining the resilience index of an urban water environment according to claim 1, characterized in that: The target urban area includes a plurality of computing units; The water quality index of each of the N predetermined risk levels is obtained based on the water quality data of the target urban area in the M time periods, including: For any i-th predetermined risk level, the following operations are performed, wherein: : Determining at least one target time period corresponding to the i-th predetermined risk level among the M time periods; Obtaining a water quality score for each calculation unit within the target time period based on the water quality data of each calculation unit within the target time period, wherein water quality data in different concentration ranges correspond to different water quality scores; Obtaining a maximum water quality score for each calculation unit within the M time periods based on the water quality data of each calculation unit within the M time periods; Calculate the water quality index of each calculation unit in the target time period according to the water quality score of each calculation unit in the target time period and the maximum water quality score of each calculation unit in the M time periods, and obtain the water quality index of each of the multiple calculation units in the target time period; The water quality index of the i-th predetermined risk level is calculated according to the respective water quality indexes of the plurality of calculation units within the target time period to obtain the respective water quality indexes of the N predetermined risk levels.

3. The method for determining the resilience index of an urban water environment according to claim 1, characterized in that: The precipitation data includes one or more of the following: monthly total, rainfall per session, maximum daily rainfall, longest rainy period, longest rainless period, maximum continuous rainfall, and number of rainy days with different rainfall intensity thresholds; The sponge project design data includes one or more of the runoff control rate, peak flow reduction rate, rainwater resource utilization rate, pollutant removal efficiency, permeable pavement coverage rate, and storage facility capacity.

4. The method for determining the resilience index of an urban water environment according to claim 1, wherein: Determining the risk level corresponding to each of the M time periods based on the hydrological data of the target urban area within the M time periods includes: Calculate the mean and variance of the hydrological data based on the hydrological data of the target urban area within the M time periods; The risk level corresponding to each of the M time periods is determined according to the hydrological data, the average value, and the variance.

5. The method for determining the resilience index of an urban water environment according to claim 4, characterized in that: The N predetermined risk levels include no risk level, low risk level, relatively low risk level, medium risk level, relatively high risk level and high risk level; Determining the risk level corresponding to each of the M time periods according to the hydrological data, the average value, and the variance includes: The hydrological data are The risk level of the time period within the range is determined to be the no-risk level, and the corresponding hydrological index is 0; The hydrological data are The risk level of the time period within the range is determined to be the low risk level, and the corresponding hydrological index is 20%; The hydrological data are The risk level of the time period within the range is determined to be the lower risk level, and the corresponding hydrological index is 40%; The hydrological data are The risk level of the time period within the range is determined to be the medium risk level, and the corresponding hydrological index is 60%; The hydrological data are The risk level of the time period within the range is determined to be the higher risk level, and the corresponding hydrological index is 80%; The hydrological data are The risk level of the time period within the range is determined to be the high risk level, and the corresponding hydrological index is 100%; in, is the mean value of the hydrological data, S is the variance of the hydrological data, is the maximum value of the hydrological data.

6. The method for determining the resilience index of an urban water environment according to claim 1, characterized in that: The water quality data includes one or more of dissolved oxygen, ammonia nitrogen, total phosphorus, and chemical oxygen demand.

7. The method for determining the resilience index of an urban water environment according to any one of claims 1 to 6, characterized in that: Determining the resilience index of the water environment of the target urban area according to the water quality index and the hydrological index of each of the N predetermined risk levels includes: Drawing a water quality-hydrology curve according to the water quality index and the hydrological index of each of the N predetermined risk levels, wherein the water quality-hydrology curve is a curve showing changes in the water quality index as the hydrological index changes; The water quality-hydrology curve is integrated to obtain a resilience index of the water environment in the target urban area.

8. A device for determining the resilience index of an urban water environment, characterized in that: include: A first determination module is configured to determine a risk level corresponding to each of M time periods based on hydrological data of a target urban area within the M time periods, wherein the risk level corresponding to each time period is one of N predetermined risk levels, and the N predetermined risk levels correspond to N different hydrological indices according to risk level values, where M and N are each independently integers greater than or equal to 1, and the hydrological data includes at least one of precipitation data and sponge project design data; an obtaining module, configured to obtain a water quality index for each of the N predetermined risk levels based on water quality data of the target urban area during the M time periods, wherein the water quality data includes physical and chemical property data of water in the target urban area, and the water quality index is used to represent the degree of fluctuation of the water environment in the target urban area corresponding to each predetermined risk level; A second determination module determines a resilience index of the water environment of the target urban area according to the water quality index and the hydrological index of each of the N predetermined risk levels; Wherein, the obtaining module includes a second determining submodule, a first obtaining submodule, a second obtaining submodule and a second calculating submodule; The second determining submodule is configured to determine at least one target time period corresponding to the i-th predetermined risk level among the M time periods, wherein: ; The first obtaining submodule is used to obtain the water quality score of the target time period based on the water quality data of the target city area within the target time period, wherein water quality data in different concentration ranges correspond to different water quality scores; The second obtaining submodule is used to obtain the maximum water quality score of the M time periods based on the water quality data of the target urban area in the M time periods; The second calculation submodule is configured to calculate the water quality index of the i-th predetermined risk level according to the water quality score of the target time period and the maximum water quality score of the M time periods, so as to obtain the water quality index of each of the N predetermined risk levels.

9. An electronic device comprising: one or more processors; a memory for storing one or more programs, When the one or more programs are executed by the one or more processors, the one or more processors implement the method according to any one of claims 1 to 7.

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