Water shortage city rainwater runoff sewage separation method and system

Abstract

The present application relates to the technical field of urban rainwater management, and in particular to a water-deficient city rainwater runoff pollution separation method and system. An easy water accumulation section distribution map and a rainwater pipe network distribution map are obtained to determine a sedimentation risk pipe section; an initial interception index is determined according to rainfall data; a starting shear stress is determined according to a continuous rain-free duration; an effective shear stress in the pipe is calculated in the separation stage; when the effective shear stress is not less than the starting shear stress, a pollution propagation speed is calculated; a predicted time for pollutants to reach a separation node is calculated according to the pollution propagation speed; and when the predicted time and the pollution propagation speed meet the requirements, rainwater runoff is guided into a sewage treatment path. The present application dynamically tracks and predicts the movement process of a lagging pollution peak through double monitoring points, thereby improving rainwater resource utilization.

Description

Technical Field

[0001] This invention relates to the field of urban stormwater management technology, specifically a method and system for separating stormwater runoff from sewage in water-scarce cities. Background Technology

[0002] For water-scarce cities, rainwater is not only a potential source of pollution but also an important water resource. To avoid direct discharge of highly polluted rainwater in the early stages and to prevent the waste of usable rainwater later, existing methods typically determine the degree of rainwater pollution based on rainfall time or amount, and then separate clean and polluted rainwater runoff.

[0003] However, water-scarce cities experience prolonged droughts, leading to the accumulation of large amounts of deposited pollutants on the underlying surface and within pipe systems. These deposits may only be stirred up by strong currents during the later stages of rainfall, potentially delaying the peak pollution levels. Current diversion assessments primarily rely on time or indicators such as suspended solids in the water, failing to detect these solid deposited pollutants. Failure to identify them promptly can easily result in incorrect assessments of cleanup and pollution control, hindering pollution reduction efforts and impacting rainwater reuse.

[0004] Therefore, there is an urgent need for a method and system for separating stormwater runoff into clean and polluted areas in water-scarce cities, which can take into account the deposited pollutants in the pipe network and improve the accuracy of the clean and polluted area separation judgment. Summary of the Invention

[0005] (1) Technical problems to be solved

[0006] The purpose of this invention is to provide a method and system for separating clean and polluted runoff in water-scarce cities, in order to solve the problem that the delayed release of deposited pollutants in rainwater runoff during post-drought rainfall in water-scarce cities is difficult to accurately identify, thus leading to misjudgment of clean and polluted runoff separation.

[0007] (2) Technical solution

[0008] To achieve the above objectives, on the one hand, the present invention provides a method for separating clean and polluted stormwater runoff in water-scarce cities, the method comprising:

[0009] Step S1: Obtain the distribution map of easily flooded road sections and the distribution map of stormwater pipe network in the city; spatially match the distribution map of easily flooded road sections with the distribution map of stormwater pipe network to determine the pipe sections with deposition risk; obtain rainfall data, including the start time of the rainfall and the duration of continuous rainless period before the start; determine the initial interception index based on the rainfall data; from the start of rainfall until the initial interception index is met, divert the stormwater runoff entering the diversion node into the sewage treatment path; after the initial interception index is met, enter the diversion stage and divert the stormwater runoff entering the diversion node into the stormwater reuse path.

[0010] Step S2: Sequentially set up a first monitoring point and a second monitoring point along the water flow direction in the pipeline section with deposition risk; during the diversion stage, collect the first water quality data and the first hydraulic data of the first monitoring point, and the second water quality data and the second hydraulic data of the second monitoring point; determine the starting shear stress of the deposited pollutants by querying a preset correspondence based on the continuous rainless period; calculate the effective shear stress in the pipeline based on the first hydraulic data and the second hydraulic data; when the effective shear stress is not less than the starting shear stress, calculate the pollution propagation speed based on the first water quality data and the second water quality data.

[0011] Step S3: Calculate the predicted time for pollutants to reach the diversion node based on the pollution propagation speed and the distance between the second monitoring point and the diversion node; when the predicted time is less than the preset control response time and the pollution propagation speed is not lower than the preset propagation speed threshold, guide the rainwater runoff into the sewage treatment path.

[0012] Preferably, the method for sequentially setting a first monitoring point and a second monitoring point along the water flow direction in the sedimentation risk pipeline section includes:

[0013] Based on the stormwater pipe network distribution map, determine the upstream inlet location and the downstream outlet location near the diversion node of the pipeline section with deposition risk; within the pipeline section with deposition risk, determine the pipeline path between the upstream inlet location and the downstream outlet location.

[0014] Based on the diversion node, the minimum interval distance between the first monitoring point and the second monitoring point on the pipeline path is calculated according to the continuous rainless period and the preset control response time. On the pipeline path, manholes that meet the minimum interval distance condition and have the conditions for installing monitoring equipment are set as the first monitoring point and the second monitoring point, and the distance between the first monitoring point and the diversion node is greater than the distance between the second monitoring point and the diversion node.

[0015] Preferably, the method for calculating the minimum interval distance between the first monitoring point and the second monitoring point on the pipeline path based on the continuous rainless period and the preset control response time includes:

[0016] Obtain the pipe diameter, longitudinal slope, and roughness of the pipeline section with deposition risk; calculate the average thickness of the sediment based on the continuous rainless period; correct the pipe diameter based on the average thickness of the sediment to determine the effective flow cross-section.

[0017] Based on the effective flow cross-section, longitudinal slope, and roughness, the theoretical flow velocity of the pipeline path is calculated using the Manning formula; based on the theoretical flow velocity and the preset control response time, the minimum interval distance between the first monitoring point and the second monitoring point is calculated.

[0018] Preferably, the method for calculating the pollution propagation speed based on the first water quality data and the second water quality data includes:

[0019] The first and second water quality data are synchronized and filtered to obtain a first and second water quality sequence with a unified time reference. A time window of a preset length is selected from the starting period of the first water quality sequence, and the mean value of the first water quality data within the time window is calculated to obtain the background value. In the first water quality sequence, the first complete waveform that rises from the background value to the peak value and then falls back to the background value is identified and defined as a reference waveform template. On the second water quality sequence, a sliding window with a duration equal to that of the reference waveform template is set. The normalized cross-correlation coefficient sequence between the second water quality data and the reference waveform template within the sliding window is calculated.

[0020] The center point of the sliding window is located based on the maximum normalized cross-correlation coefficient in the normalized cross-correlation coefficient sequence; the time difference between the center point of the sliding window and the starting time point of the reference waveform template is calculated as the time offset of sediment propagation from the first monitoring point to the second monitoring point; when the time offset is greater than 0 and the maximum normalized cross-correlation coefficient is greater than a preset correlation intensity threshold, the pollution propagation speed is calculated based on the time offset and the pipe length between the first and second monitoring points.

[0021] Preferably, the method for calculating the normalized cross-correlation sequence between the second water quality data within the sliding window and the reference waveform template includes:

[0022] Perform a Fast Fourier Transform on the reference waveform template to obtain the reference waveform template spectrum; perform a Fast Fourier Transform on the data within the sliding window to obtain the sliding window data spectrum; and pass the reference waveform template spectrum through a low-pass filter to obtain the filtered reference waveform template spectrum.

[0023] The frequency domain cross-correlation result is obtained by calculating the conjugate product of the spectrum of the filtered reference waveform template and the spectrum of the sliding window data; the frequency domain cross-correlation result is subjected to inverse fast Fourier transform to obtain a time domain sequence; the time domain sequence is normalized to obtain a normalized cross-correlation coefficient sequence.

[0024] Based on the same inventive concept, this invention also provides a stormwater runoff separation system for water-scarce cities, the system comprising:

[0025] The initial interception and scene recognition module is used to acquire distribution maps of easily flooded road sections and stormwater pipe networks in the city; spatially match the distribution maps of easily flooded road sections and stormwater pipe networks to determine pipe sections with deposition risk; acquire rainfall data, including the start time of the rainfall and the duration of continuous rainless periods before it begins; determine initial interception indicators based on the rainfall data; during the period from the start of rainfall until the initial interception indicators are met, guide the stormwater runoff entering the diversion node into the sewage treatment path; after the initial interception indicators are met, the diversion stage begins, and the stormwater runoff entering the diversion node is guided into the stormwater reuse path.

[0026] The deposition release identification and propagation determination module is used to sequentially set a first monitoring point and a second monitoring point along the water flow direction in the pipeline section with deposition risk; during the diversion stage, it collects the first water quality data and the first hydraulic data of the first monitoring point, as well as the second water quality data and the second hydraulic data of the second monitoring point; it determines the initiation shear stress of the deposited pollutants by querying a preset correspondence based on the continuous rainless period; it calculates the effective shear stress in the pipeline based on the first hydraulic data and the second hydraulic data; when the effective shear stress is not less than the initiation shear stress, it calculates the pollution propagation speed based on the first water quality data and the second water quality data.

[0027] The diversion control execution module is used to calculate the predicted time for pollutants to reach the diversion node based on the pollution propagation speed and the distance between the second monitoring point and the diversion node; when the predicted time is less than the preset control response time and the pollution propagation speed is not lower than the preset propagation speed threshold, the rainwater runoff is directed into the sewage treatment path.

[0028] Preferably, the deposition release identification and propagation determination module includes:

[0029] The monitoring point setting module is used to determine the upstream inlet position and the downstream outlet position near the diversion node of the sedimentation risk pipeline section according to the rainwater pipe network distribution map; and to determine the pipeline path between the upstream inlet position and the downstream outlet position within the sedimentation risk pipeline section.

[0030] Based on the diversion node, the minimum interval distance between the first monitoring point and the second monitoring point on the pipeline path is calculated according to the continuous rainless period and the preset control response time. On the pipeline path, manholes that meet the minimum interval distance condition and have the conditions for installing monitoring equipment are set as the first monitoring point and the second monitoring point, and the distance between the first monitoring point and the diversion node is greater than the distance between the second monitoring point and the diversion node.

[0031] Preferably, the monitoring point setting module includes:

[0032] The minimum spacing calculation module is used to obtain the pipe diameter, longitudinal slope, and roughness of the pipeline section with deposition risk; calculate the average thickness of sediment based on the continuous rainless period; and correct the pipe diameter based on the average thickness of sediment to determine the effective flow cross section.

[0033] Based on the effective flow cross-section, longitudinal slope, and roughness, the theoretical flow velocity of the pipeline path is calculated using the Manning formula; based on the theoretical flow velocity and the preset control response time, the minimum interval distance between the first monitoring point and the second monitoring point is calculated.

[0034] Preferably, the deposition release identification and propagation determination module includes:

[0035] The pollution propagation speed calculation module is used to synchronize and filter the first and second water quality data to obtain a first and second water quality sequence with a unified time reference; select a time window of a preset length from the starting period of the first water quality sequence, and calculate the mean value of the first water quality data within the time window to obtain the background value; in the first water quality sequence, identify the first complete waveform that rises from the background value to the peak value and then falls back to the background value, and define it as a reference waveform template; on the second water quality sequence, set a sliding window with a duration equal to that of the reference waveform template; and calculate the normalized cross-correlation coefficient sequence between the second water quality data and the reference waveform template within the sliding window.

[0036] The center point of the sliding window is located based on the maximum normalized cross-correlation coefficient in the normalized cross-correlation coefficient sequence; the time difference between the center point of the sliding window and the starting time point of the reference waveform template is calculated as the time offset of sediment propagation from the first monitoring point to the second monitoring point; when the time offset is greater than 0 and the maximum normalized cross-correlation coefficient is greater than a preset correlation intensity threshold, the pollution propagation speed is calculated based on the time offset and the pipe length between the first and second monitoring points.

[0037] Preferably, the pollution propagation speed calculation module includes:

[0038] The normalized cross-correlation coefficient calculation module is used to perform a fast Fourier transform on the reference waveform template to obtain the reference waveform template spectrum; perform a fast Fourier transform on the data within the sliding window to obtain the sliding window data spectrum; and pass the reference waveform template spectrum through a low-pass filter to obtain the filtered reference waveform template spectrum.

[0039] The frequency domain cross-correlation result is obtained by calculating the conjugate product of the spectrum of the filtered reference waveform template and the spectrum of the sliding window data; the frequency domain cross-correlation result is subjected to inverse fast Fourier transform to obtain a time domain sequence; the time domain sequence is normalized to obtain a normalized cross-correlation coefficient sequence.

[0040] (3) Beneficial effects

[0041] Compared with the prior art, the beneficial effects of the present invention are:

[0042] 1. Set up dual monitoring points according to the pipeline section with deposition risk, and realize the early identification of the resuspension behavior of deposited pollutants by inverting the pollution waveform propagation speed. This can complete the diversion and switching before the pollution reaches the diversion node, improving the real-time performance and accuracy of clean and polluted diversion.

[0043] 2. By determining the starting shear stress through the coupling of continuous rainless period and hydraulic conditions, the interception response can adapt to the characteristics of large-scale accumulation of pollutants after drought in water-scarce cities, thereby reducing unnecessary interception of reusable rainwater while ensuring pollution control. Attached Figure Description

[0044] Figure 1 This is a flowchart of a method for separating stormwater runoff from sewage in water-scarce cities according to Embodiment 1 of the present invention;

[0045] Figure 2 This is a block diagram of a stormwater runoff separation system for water-scarce cities according to Embodiment 2 of the present invention. Detailed Implementation

[0046] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0047] Before providing examples, it's necessary to describe the application scenario of this invention. In the stormwater drainage networks of water-scarce cities, low-lying areas prone to water accumulation are the main entry points for surface pollutants to migrate into the pipes. During prolonged dry seasons, a single period of more than 72 hours without rain is sufficient to form a complex sediment at the bottom of the pipes, consisting of fine-grained silt and adsorbed tire wear particles, heavy metals, and organic matter. As the drought extends to a week or even longer, these sediments gradually lose water and compact in a static environment, increasing their cohesion and significantly increasing the hydraulic shear force required to initiate flushing. When rainfall occurs, the initial runoff first flushes the pipe walls and bottom, but only when the flow rate increases and the velocity exceeds the critical initiation velocity can these compacted sediment layers be effectively eroded and suspended. This physical process results in a significant delay in pollutant release; the formation and arrival of high-concentration pollution plumes at monitoring points lag behind simple predictions based on the start time of rainfall or the initial runoff water quality.

[0048] Example 1: As Figure 1 As shown in the figure, this embodiment provides a method for separating clean and polluted stormwater runoff in water-scarce cities. The method includes:

[0049] Step S1: Obtain the distribution map of easily flooded road sections and the distribution map of stormwater pipe network in the city; spatially match the distribution map of easily flooded road sections with the distribution map of stormwater pipe network to determine the pipe sections with deposition risk; obtain rainfall data, including the start time of the rainfall and the duration of continuous rainless period before the start; determine the initial interception index based on the rainfall data; from the start of rainfall until the initial interception index is met, divert the stormwater runoff entering the diversion node into the sewage treatment path; after the initial interception index is met, enter the diversion stage and divert the stormwater runoff entering the diversion node into the stormwater reuse path.

[0050] Step S2: Sequentially set up a first monitoring point and a second monitoring point along the water flow direction in the pipeline section with deposition risk; during the diversion stage, collect the first water quality data and the first hydraulic data of the first monitoring point, and the second water quality data and the second hydraulic data of the second monitoring point; determine the starting shear stress of the deposited pollutants by querying a preset correspondence based on the continuous rainless period; calculate the effective shear stress in the pipeline based on the first hydraulic data and the second hydraulic data; when the effective shear stress is not less than the starting shear stress, calculate the pollution propagation speed based on the first water quality data and the second water quality data.

[0051] Step S3: Calculate the predicted time for pollutants to reach the diversion node based on the pollution propagation speed and the distance between the second monitoring point and the diversion node; when the predicted time is less than the preset control response time and the pollution propagation speed is not lower than the preset propagation speed threshold, guide the rainwater runoff into the sewage treatment path.

[0052] For example, taking a water-scarce city A as an example, the drainage system is a separate system, separating rainwater runoff from domestic sewage. Rainwater runoff is further divided into recyclable and non-recyclable streams, switched using diversion nodes. A diversion node is a key node in the rainwater pipe network equipped with a controllable diversion weir and an electric gate, capable of switching water flow to a sewage treatment plant or rainwater reuse pond according to control commands. During implementation, firstly, a distribution map of easily flooded road sections and a rainwater pipe network distribution map are obtained. In GIS software, the easily flooded road section layer and the rainwater pipe network layer are overlaid to identify the downstream pipe sections directly corresponding to each easily flooded road section. These downstream pipe sections are marked as pipe sections with deposition risk requiring key monitoring. Rainfall data is obtained through the real-time data interface of the municipal meteorological bureau, including the start time of this rainfall and the duration of continuous rainless periods of 108 hours prior to its start. Based on historical rainwater pollution monitoring data, the initial rainwater pollution load is mainly concentrated in the first 2-5 mm of rainfall at the beginning of the rainfall event. Considering water quality safety requirements, the duration corresponding to the first 3 mm of rainfall is selected as the initial interception index. The catchment area of ​​the diversion node was determined to be A = 18.6 ha using GIS data. Based on the impermeability ratio of the road, a runoff coefficient of C = 0.88 was selected. The initial interception time was calculated using the pipeline design inflow rate Q = 0.15 m³ / s under the corresponding return period conditions. Seconds. When rainwater is introduced into the wastewater treatment path at the diversion node for 6 minutes, the diversion phase begins to ensure that the initial polluted rainwater is treated.

[0053] The first water quality and hydraulic data were collected from the first monitoring point located in the upstream inspection well of the pipeline section at the sedimentation risk, and the second water quality and hydraulic data were collected from the second monitoring point located in the downstream inspection well, at a frequency of 1 Hz. For example, turbidity was collected as a water quality indicator using an online turbidity meter, and water flow velocity was collected as a hydraulic indicator using a Doppler current meter. Turbidity was chosen because it can quickly respond to changes in the concentration of suspended particulate matter in the water and directly reflect the resuspension of sediments; flow velocity was chosen because it is a key parameter for calculating the shear force of the water flow and directly determines the sediment initiation and transport capacity.

[0054] Based on a 108-hour period of continuous rainlessness, a pre-defined correlation was used to determine the starting shear stress as 2.4 Pascals. Specifically, this pre-defined correlation was established through standard hydraulic experiments, including collecting representative sediment samples from the pipeline section at the deposition risk, determining the critical starting conditions through a series of scouring experiments at different flow velocities, and fitting the correlation between hydraulic shear theory and the duration of continuous rainlessness to construct the pre-defined correlation. Based on the flow velocity data from two monitoring points, and using the hydraulic shear stress formula τ=ρgRS (where ρ is the density of water, g is the acceleration due to gravity, R is the hydraulic radius, and S is the hydraulic gradient), the effective shear stress within the pipeline was calculated to be 2.9 Pascals. Since 2.9 is not less than 2.4, the temporal characteristics of the turbidity data from the two monitoring points were analyzed, and the pollution propagation velocity was calculated to be 0.43 m / s. Considering the distance of the second monitoring point from the diversion node (75 meters), the predicted time was calculated to be 174 seconds. If the predicted time is less than the preset control response time of 180 seconds, and the pollution propagation speed is not lower than the preset propagation speed threshold of 0.35 m / s, the system immediately generates a control command to switch the diversion node from the rainwater reuse path to the wastewater treatment path. Specifically, the preset control response time includes the maximum time for the entire process of data acquisition, algorithm calculation, and valve action, and the preset propagation speed threshold is determined based on the statistical percentile of the pipeline design flow velocity and the propagation speed of historical pollution events.

[0055] The method of sequentially setting a first monitoring point and a second monitoring point along the water flow direction in the pipeline section with sedimentation risk includes:

[0056] Based on the stormwater pipe network distribution map, determine the upstream inlet location and the downstream outlet location near the diversion node of the pipeline section with deposition risk; within the pipeline section with deposition risk, determine the pipeline path between the upstream inlet location and the downstream outlet location.

[0057] Based on the diversion node, the minimum interval distance between the first monitoring point and the second monitoring point on the pipeline path is calculated according to the continuous rainless period and the preset control response time. On the pipeline path, manholes that meet the minimum interval distance condition and have the conditions for installing monitoring equipment are set as the first monitoring point and the second monitoring point, and the distance between the first monitoring point and the diversion node is greater than the distance between the second monitoring point and the diversion node.

[0058] The method for calculating the minimum interval distance between the first monitoring point and the second monitoring point on the pipeline path based on the duration of continuous rainlessness and the preset control response time includes:

[0059] Obtain the pipe diameter, longitudinal slope, and roughness of the pipeline section with deposition risk; calculate the average thickness of the sediment based on the continuous rainless period; correct the pipe diameter based on the average thickness of the sediment to determine the effective flow cross-section.

[0060] Based on the effective flow cross-section, longitudinal slope, and roughness, the theoretical flow velocity of the pipeline path is calculated using the Manning formula; based on the theoretical flow velocity and the preset control response time, the minimum interval distance between the first monitoring point and the second monitoring point is calculated.

[0061] For example, the upstream inlet manhole K4-06 and downstream outlet manhole K4-10 of the sedimentation risk pipeline section have a downstream diversion node within manhole K4-11. The total length of the pipeline path between K4-06 and K4-10 is 245 meters, and the pipeline material is concrete. Based on a continuous dry season of 108 hours and a preset control response time of 180 seconds, the minimum interval distance required between the first and second monitoring points is calculated. The pipe section has a diameter of 800 mm, a longitudinal slope of 0.003, and a roughness coefficient of 0.013. Based on a continuous dry season of 108 hours, an empirical formula is obtained through regression analysis based on local historical sediment thickness monitoring data. The estimated average thickness of the sediments is 8 mm, of which, and These are parameters obtained by fitting local monitoring data. For the duration of continuous rainless periods, The correction coefficient for easily flooded sections is obtained from actual sampling measurements. Based on this, the pipe diameter is corrected, resulting in an effective flow diameter of 784 mm and a corresponding effective flow cross-sectional area of ​​0.483 square meters. The hydraulic radius is calculated to be 196 mm based on the effective flow diameter of 784 mm, and the theoretical flow velocity along the pipe path is calculated to be 0.85 m / s using the Manning formula. Finally, based on the theoretical flow velocity and the preset control response time of 180 seconds, the minimum interval distance is calculated to be 0.85 × 180 = 153 meters. After determining the minimum interval distance, manhole K4-09 is selected as the second monitoring point, 75 meters from the diversion node; manhole K4-07 is selected as the first monitoring point, with an actual pipe distance of 160 meters between it and the second monitoring point. It should be noted that in actual engineering, the location of the manholes is fixed; therefore, the layout of the monitoring points needs to strike a balance between theoretical calculations and engineering conditions.

[0062] The method for calculating the pollution propagation speed based on the first water quality data and the second water quality data includes:

[0063] The first and second water quality data are synchronized and filtered to obtain a first and second water quality sequence with a unified time reference. A time window of a preset length is selected from the starting period of the first water quality sequence, and the mean value of the first water quality data within the time window is calculated to obtain the background value. In the first water quality sequence, the first complete waveform that rises from the background value to the peak value and then falls back to the background value is identified and defined as a reference waveform template. On the second water quality sequence, a sliding window with a duration equal to that of the reference waveform template is set. The normalized cross-correlation coefficient sequence between the second water quality data and the reference waveform template within the sliding window is calculated.

[0064] The center point of the sliding window is located based on the maximum normalized cross-correlation coefficient in the normalized cross-correlation coefficient sequence; the time difference between the center point of the sliding window and the starting time point of the reference waveform template is calculated as the time offset of sediment propagation from the first monitoring point to the second monitoring point; when the time offset is greater than 0 and the maximum normalized cross-correlation coefficient is greater than a preset correlation intensity threshold, the pollution propagation speed is calculated based on the time offset and the pipe length between the first and second monitoring points.

[0065] The method for calculating the normalized cross-correlation sequence between the second water quality data within the sliding window and the reference waveform template includes:

[0066] Perform a Fast Fourier Transform on the reference waveform template to obtain the reference waveform template spectrum; perform a Fast Fourier Transform on the data within the sliding window to obtain the sliding window data spectrum; and pass the reference waveform template spectrum through a low-pass filter to obtain the filtered reference waveform template spectrum.

[0067] The frequency domain cross-correlation result is obtained by calculating the conjugate product of the spectrum of the filtered reference waveform template and the spectrum of the sliding window data; the frequency domain cross-correlation result is subjected to inverse fast Fourier transform to obtain a time domain sequence; the time domain sequence is normalized to obtain a normalized cross-correlation coefficient sequence.

[0068] For example, turbidity data collected from the first monitoring point K4-07 and the second monitoring point K4-09 were synchronized at millisecond levels using a GPS module. The raw turbidity data collected at a frequency of 1Hz was smoothed using a Savitzky-Golay filter to eliminate random fluctuation interference. The background value was calculated to be 8.6 NTU from the first 5 minutes of data in the first water quality sequence. Subsequently, the first complete waveform was identified in the first water quality sequence: it started from 8.6 NTU, rose to a peak of 187 NTU at 3 minutes and 42 seconds, and finally fell back to 9.1 NTU, with the entire process lasting 6 minutes and 28 seconds. This waveform was defined as the reference waveform template. In the second water quality sequence, a sliding window with the same duration as the reference waveform template (6 minutes and 28 seconds) was taken. The reference waveform template was subjected to FFT transformation to obtain its spectral representation. This spectrum was then low-pass filtered with a cutoff frequency of 0.5Hz to simulate high-frequency attenuation during pollutant transport. It was then multiplied by conjugate with the spectrum of the sliding window data and subjected to inverse FFT transformation to finally obtain the normalized cross-correlation coefficient sequence. The cutoff frequency of 0.5 Hz was determined by analyzing the dominant frequency energy distribution of turbidity waveforms in historical pollution events.

[0069] The maximum value of this sequence is 0.86, exceeding the preset correlation coefficient threshold of 0.75, corresponding to a sliding window center point timestamp of 14 minutes and 25 seconds. The reference waveform template starts at 8 minutes and 10 seconds, resulting in a calculated time offset of 375 seconds. Combined with the 160-meter pipeline distance between the two monitoring points, the pollution propagation speed is calculated to be 0.43 meters per second. It should be noted that the frequency domain cross-correlation method effectively overcomes waveform distortion and attenuation during transmission, exhibiting better robustness compared to traditional time-domain methods. The preset correlation coefficient threshold is the lower bound of the confidence interval based on the statistical results of cross-correlation of effective pollution events over the years.

[0070] Example 2: Based on the same inventive concept, such as Figure 2 As shown, this embodiment also provides a stormwater runoff separation system for water-scarce cities, the system comprising:

[0071] The initial interception and scene recognition module is used to acquire distribution maps of easily flooded road sections and stormwater pipe networks in the city; spatially match the distribution maps of easily flooded road sections and stormwater pipe networks to determine pipe sections with deposition risk; acquire rainfall data, including the start time of the rainfall and the duration of continuous rainless periods before it begins; determine initial interception indicators based on the rainfall data; during the period from the start of rainfall until the initial interception indicators are met, guide the stormwater runoff entering the diversion node into the sewage treatment path; after the initial interception indicators are met, the diversion stage begins, and the stormwater runoff entering the diversion node is guided into the stormwater reuse path.

[0072] The deposition release identification and propagation determination module is used to sequentially set a first monitoring point and a second monitoring point along the water flow direction in the pipeline section with deposition risk; during the diversion stage, it collects the first water quality data and the first hydraulic data of the first monitoring point, as well as the second water quality data and the second hydraulic data of the second monitoring point; it determines the initiation shear stress of the deposited pollutants by querying a preset correspondence based on the continuous rainless period; it calculates the effective shear stress in the pipeline based on the first hydraulic data and the second hydraulic data; when the effective shear stress is not less than the initiation shear stress, it calculates the pollution propagation speed based on the first water quality data and the second water quality data.

[0073] The diversion control execution module is used to calculate the predicted time for pollutants to reach the diversion node based on the pollution propagation speed and the distance between the second monitoring point and the diversion node; when the predicted time is less than the preset control response time and the pollution propagation speed is not lower than the preset propagation speed threshold, the rainwater runoff is directed into the sewage treatment path.

[0074] The deposition release identification and propagation determination module includes:

[0075] The monitoring point setting module is used to determine the upstream inlet position and the downstream outlet position near the diversion node of the sedimentation risk pipeline section according to the rainwater pipe network distribution map; and to determine the pipeline path between the upstream inlet position and the downstream outlet position within the sedimentation risk pipeline section.

[0076] Based on the diversion node, the minimum interval distance between the first monitoring point and the second monitoring point on the pipeline path is calculated according to the continuous rainless period and the preset control response time. On the pipeline path, manholes that meet the minimum interval distance condition and have the conditions for installing monitoring equipment are set as the first monitoring point and the second monitoring point, and the distance between the first monitoring point and the diversion node is greater than the distance between the second monitoring point and the diversion node.

[0077] The monitoring point setting module includes:

[0078] The minimum spacing calculation module is used to obtain the pipe diameter, longitudinal slope, and roughness of the pipeline section with deposition risk; calculate the average thickness of sediment based on the continuous rainless period; and correct the pipe diameter based on the average thickness of sediment to determine the effective flow cross section.

[0079] Based on the effective flow cross-section, longitudinal slope, and roughness, the theoretical flow velocity of the pipeline path is calculated using the Manning formula; based on the theoretical flow velocity and the preset control response time, the minimum interval distance between the first monitoring point and the second monitoring point is calculated.

[0080] The deposition release identification and propagation determination module includes:

[0081] The pollution propagation speed calculation module is used to synchronize and filter the first and second water quality data to obtain a first and second water quality sequence with a unified time reference; select a time window of a preset length from the starting period of the first water quality sequence, and calculate the mean value of the first water quality data within the time window to obtain the background value; in the first water quality sequence, identify the first complete waveform that rises from the background value to the peak value and then falls back to the background value, and define it as a reference waveform template; on the second water quality sequence, set a sliding window with a duration equal to that of the reference waveform template; and calculate the normalized cross-correlation coefficient sequence between the second water quality data and the reference waveform template within the sliding window.

[0082] The center point of the sliding window is located based on the maximum normalized cross-correlation coefficient in the normalized cross-correlation coefficient sequence; the time difference between the center point of the sliding window and the starting time point of the reference waveform template is calculated as the time offset of sediment propagation from the first monitoring point to the second monitoring point; when the time offset is greater than 0 and the maximum normalized cross-correlation coefficient is greater than a preset correlation intensity threshold, the pollution propagation speed is calculated based on the time offset and the pipe length between the first and second monitoring points.

[0083] The pollution propagation speed calculation module includes:

[0084] The normalized cross-correlation coefficient calculation module is used to perform a fast Fourier transform on the reference waveform template to obtain the reference waveform template spectrum; perform a fast Fourier transform on the data within the sliding window to obtain the sliding window data spectrum; and pass the reference waveform template spectrum through a low-pass filter to obtain the filtered reference waveform template spectrum.

[0085] The frequency domain cross-correlation result is obtained by calculating the conjugate product of the spectrum of the filtered reference waveform template and the spectrum of the sliding window data; the frequency domain cross-correlation result is subjected to inverse fast Fourier transform to obtain a time domain sequence; the time domain sequence is normalized to obtain a normalized cross-correlation coefficient sequence.

[0086] It should be noted that the specific methods by which each module performs operations in the system described in the above embodiments have been described in detail in the embodiments related to the method, and will not be elaborated here.

[0087] Finally, it should be noted that although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for separating stormwater runoff into clean and polluted areas in water-scarce cities, characterized in that, The method includes: Obtain a map showing the distribution of flood-prone road sections and stormwater drainage network in the city; spatially match the map with the stormwater drainage network to identify pipeline sections at risk of sedimentation; acquire rainfall data, including the start time of the rainfall and the duration of continuous dry weather prior to it; determine initial interception targets based on the rainfall data; during the period from the start of rainfall until the initial interception targets are met, divert stormwater runoff entering the diversion node to the wastewater treatment path; after the initial interception targets are met, enter the diversion stage and divert stormwater runoff entering the diversion node to the stormwater reuse path; A first monitoring point and a second monitoring point are sequentially set along the water flow direction in the pipeline section at the deposition risk. During the diversion phase, first water quality data and first hydraulic data are collected from the first monitoring point, and second water quality data and second hydraulic data are collected from the second monitoring point. The initiation shear stress of the deposited pollutants is determined by querying a preset correspondence based on the duration of continuous rainlessness. The effective shear stress in the pipeline is calculated based on the first and second hydraulic data. When the effective shear stress is not less than the initiation shear stress, the pollution propagation speed is calculated based on the first and second water quality data. The predicted time for pollutants to reach the diversion node is calculated based on the pollution propagation speed and the distance between the second monitoring point and the diversion node; when the predicted time is less than the preset control response time and the pollution propagation speed is not lower than the preset propagation speed threshold, the rainwater runoff is directed into the sewage treatment path. The method for calculating the pollution propagation speed based on the first water quality data and the second water quality data includes: The first and second water quality data are synchronized and filtered to obtain a first and second water quality sequence with a unified time reference. A time window of a preset length is selected from the starting period of the first water quality sequence, and the mean value of the first water quality data within the time window is calculated to obtain the background value. In the first water quality sequence, the first complete waveform that rises from the background value to the peak value and then falls back to the background value is identified and defined as a reference waveform template. On the second water quality sequence, a sliding window with a duration equal to that of the reference waveform template is set. The normalized cross-correlation coefficient sequence between the second water quality data and the reference waveform template within the sliding window is calculated. The center point of the sliding window is located based on the maximum normalized cross-correlation coefficient in the normalized cross-correlation coefficient sequence; the time difference between the center point of the sliding window and the starting time point of the reference waveform template is calculated as the time offset of sediment propagation from the first monitoring point to the second monitoring point; when the time offset is greater than 0 and the maximum normalized cross-correlation coefficient is greater than a preset correlation intensity threshold, the pollution propagation speed is calculated based on the time offset and the pipe length between the first and second monitoring points.

2. The method for separating stormwater runoff and wastewater in water-scarce cities according to claim 1, characterized in that, The method of sequentially setting a first monitoring point and a second monitoring point along the water flow direction in the pipeline section with sedimentation risk includes: Based on the stormwater pipe network distribution map, determine the upstream inlet location and the downstream outlet location near the diversion node of the pipeline section with deposition risk; within the pipeline section with deposition risk, determine the pipeline path between the upstream inlet location and the downstream outlet location; Based on the diversion node, the minimum interval distance between the first monitoring point and the second monitoring point on the pipeline path is calculated according to the continuous rainless period and the preset control response time. On the pipeline path, manholes that meet the minimum interval distance condition and have the conditions for installing monitoring equipment are set as the first monitoring point and the second monitoring point, and the distance between the first monitoring point and the diversion node is greater than the distance between the second monitoring point and the diversion node.

3. A method for separating stormwater runoff from sewage in water-scarce cities according to claim 2, characterized in that, The method for calculating the minimum interval distance between the first monitoring point and the second monitoring point on the pipeline path based on the duration of continuous rainlessness and the preset control response time includes: Obtain the pipe diameter, longitudinal slope, and roughness of the pipeline section with deposition risk; calculate the average sediment thickness based on the continuous rainless period; correct the pipe diameter based on the average sediment thickness to determine the effective flow cross-section; Based on the effective flow cross-section, longitudinal slope, and roughness, the theoretical flow velocity of the pipeline path is calculated using the Manning formula; based on the theoretical flow velocity and the preset control response time, the minimum interval distance between the first monitoring point and the second monitoring point is calculated.

4. A method for separating stormwater runoff from sewage in water-scarce cities according to claim 3, characterized in that, The method for calculating the normalized cross-correlation sequence between the second water quality data within the sliding window and the reference waveform template includes: Perform a Fast Fourier Transform on the reference waveform template to obtain the reference waveform template spectrum; perform a Fast Fourier Transform on the data within the sliding window to obtain the sliding window data spectrum; and pass a low-pass filter on the reference waveform template spectrum to obtain the filtered reference waveform template spectrum. The frequency domain cross-correlation result is obtained by calculating the conjugate product of the spectrum of the filtered reference waveform template and the spectrum of the sliding window data; the frequency domain cross-correlation result is subjected to inverse fast Fourier transform to obtain a time domain sequence; the time domain sequence is normalized to obtain a normalized cross-correlation coefficient sequence.

5. A stormwater runoff separation system for water-scarce cities, characterized in that, The system includes: The initial interception and scene recognition module is used to acquire distribution maps of easily flooded road sections and stormwater pipe network in the city; spatially match the distribution maps of easily flooded road sections and stormwater pipe network to determine pipe sections with deposition risk; acquire rainfall data, including the start time of the rainfall and the duration of continuous rainless periods before it begins; determine initial interception indicators based on the rainfall data; from the start of rainfall until the initial interception indicators are met, guide the stormwater runoff entering the diversion node into the sewage treatment path; after the initial interception indicators are met, enter the diversion stage and guide the stormwater runoff entering the diversion node into the stormwater reuse path; The deposition release identification and propagation determination module is used to sequentially set a first monitoring point and a second monitoring point along the water flow direction in the pipeline section with deposition risk; during the diversion stage, it collects first water quality data and first hydraulic data from the first monitoring point, and second water quality data and second hydraulic data from the second monitoring point; it determines the initiation shear stress of the deposited pollutants by querying a preset correspondence based on the continuous rainless duration; it calculates the effective shear stress in the pipeline based on the first hydraulic data and the second hydraulic data; when the effective shear stress is not less than the initiation shear stress, it calculates the pollution propagation speed based on the first water quality data and the second water quality data. The diversion control execution module is used to calculate the predicted time for pollutants to reach the diversion node based on the pollution propagation speed and the distance between the second monitoring point and the diversion node; when the predicted time is less than the preset control response time and the pollution propagation speed is not lower than the preset propagation speed threshold, the rainwater runoff is directed into the sewage treatment path. The deposition release identification and propagation determination module includes: The pollution propagation speed calculation module is used to synchronize and filter the first and second water quality data to obtain a first and second water quality sequence with a unified time reference; select a time window of a preset length from the beginning period of the first water quality sequence, and calculate the mean value of the first water quality data within the time window to obtain the background value; in the first water quality sequence, identify the first complete waveform that rises from the background value to the peak value and then falls back to the background value, and define it as a reference waveform template; on the second water quality sequence, set a sliding window with a duration equal to that of the reference waveform template; calculate the normalized cross-correlation coefficient sequence between the second water quality data and the reference waveform template within the sliding window; The center point of the sliding window is located based on the maximum normalized cross-correlation coefficient in the normalized cross-correlation coefficient sequence; the time difference between the center point of the sliding window and the starting time point of the reference waveform template is calculated as the time offset of sediment propagation from the first monitoring point to the second monitoring point; when the time offset is greater than 0 and the maximum normalized cross-correlation coefficient is greater than a preset correlation intensity threshold, the pollution propagation speed is calculated based on the time offset and the pipe length between the first and second monitoring points.

6. A stormwater runoff separation system for water-scarce cities according to claim 5, characterized in that, The deposition release identification and propagation determination module includes: The monitoring point setting module is used to determine the upstream inlet position and the downstream outlet position near the diversion node of the sedimentation risk pipeline section according to the rainwater pipe network distribution map; and to determine the pipeline path between the upstream inlet position and the downstream outlet position within the sedimentation risk pipeline section. Based on the diversion node, the minimum interval distance between the first monitoring point and the second monitoring point on the pipeline path is calculated according to the continuous rainless period and the preset control response time. On the pipeline path, manholes that meet the minimum interval distance condition and have the conditions for installing monitoring equipment are set as the first monitoring point and the second monitoring point, and the distance between the first monitoring point and the diversion node is greater than the distance between the second monitoring point and the diversion node.

7. A stormwater runoff separation system for water-scarce cities according to claim 6, characterized in that, The monitoring point setting module includes: The minimum spacing calculation module is used to obtain the pipe diameter, longitudinal slope, and roughness of the pipeline section with deposition risk; calculate the average thickness of sediment based on the continuous rainless period; and correct the pipe diameter based on the average thickness of sediment to determine the effective flow cross-section. Based on the effective flow cross-section, longitudinal slope, and roughness, the theoretical flow velocity of the pipeline path is calculated using the Manning formula; based on the theoretical flow velocity and the preset control response time, the minimum interval distance between the first monitoring point and the second monitoring point is calculated.

8. A stormwater runoff separation system for water-scarce cities according to claim 7, characterized in that, The pollution propagation speed calculation module includes: The normalized cross-correlation coefficient calculation module is used to perform a fast Fourier transform on the reference waveform template to obtain the reference waveform template spectrum; perform a fast Fourier transform on the data within the sliding window to obtain the sliding window data spectrum; and pass the reference waveform template spectrum through a low-pass filter to obtain the filtered reference waveform template spectrum. The frequency domain cross-correlation result is obtained by calculating the conjugate product of the spectrum of the filtered reference waveform template and the spectrum of the sliding window data; the frequency domain cross-correlation result is subjected to inverse fast Fourier transform to obtain a time domain sequence; the time domain sequence is normalized to obtain a normalized cross-correlation coefficient sequence.

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