Urban inland inundation ponding cause intelligent analysis method

Abstract

The invention discloses an intelligent analysis method for urban inland inundation and ponding causes, relates to the technical field of urban inland inundation and ponding cause analysis, and solves the problems that in the prior art, a large number of overground and underground internet-of-things monitoring devices are built in intelligent drainage projects in various regions, and rainfall, pipe network working conditions, surface ponding, river water levels and the like are subjected to three-dimensional monitoring; however, most projects are insufficient in big data analysis capability based on three-dimensional monitoring, and lack of technical means of pipe network facility operation diagnosis and waterlogging ponding cause intelligent analysis. The method comprises the steps of obtaining waterlogging data of a target area; judging whether to carry out early warning on the ponding depth of the ponding point based on the waterlogging data; if yes, early warning information is sent out, and rainfall data is obtained; if not, continuously monitoring and judging; the waterlogging ponding cause analysis is carried out based on the waterlogging data and the rainfall data, and the technical problem is solved.

Description

Technical Field

[0001] The invention belongs to the field of urban waterlogging cause analysis, and specifically relates to an intelligent analysis method for urban waterlogging cause analysis. Background Art

[0002] Urban waterlogging refers to the phenomenon of waterlogging disasters in cities due to heavy or continuous rainfall exceeding the city's drainage capacity. The main causes of urban waterlogging are: heavy or continuous rainfall; insufficient urban drainage capacity caused by imperfect urban drainage facilities, aging pipe networks and low emission standards; a large number of hard pavements in cities, such as asphalt roads and cement roads, have poor water permeability during rainfall, are not easy to infiltrate, and are prone to forming road surface waterlogging. Urban waterlogging will have a significant impact on people's production and life, traffic and economic development, and may even cause significant loss of life or property. Establishing a real-time prediction and early warning method and system for waterlogging is of great significance for early warning of waterlogging and improving waterlogging prevention and control capabilities.

[0003] The traditional method of analyzing the causes of urban waterlogging relies on manual offline investigation and detection methods, and conducts on-site comprehensive investigation and analysis of the local terrain of the waterlogging point, the current status of the rainwater outlet, the defects of the drainage network, the relative relationship between the outlet and the river water level, the opening status of the pump station, etc., and finally outputs the analysis report of the cause of waterlogging based on manual experience and professionalism. There are problems such as low efficiency, long cycle, and lack of guidance. The existing method of analyzing the causes of urban waterlogging mainly builds a large number of above-ground and underground Internet of Things monitoring equipment in smart drainage projects in various places, and conducts three-dimensional monitoring of rainfall, pipe network conditions, surface waterlogging, river water level, etc. However, most projects lack the ability to analyze big data based on three-dimensional monitoring, and lack technical means for diagnosing the operation of pipe network facilities and intelligent analysis of the causes of waterlogging.

[0004] Therefore, the present invention proposes an intelligent analysis method for the causes of urban waterlogging to solve the above problems. Summary of the invention

[0005] The present invention aims to solve at least one of the technical problems existing in the prior art; to this end, the present invention proposes an intelligent analysis method for the causes of urban waterlogging, which is used to solve the technical problem that the prior art has built a large number of above-ground and underground Internet of Things monitoring equipment in smart drainage projects in various places, and carried out three-dimensional monitoring of rainfall, pipeline network conditions, surface waterlogging, river water levels, etc., but most projects have insufficient big data analysis capabilities based on three-dimensional monitoring, and lack technical means for pipeline facility operation diagnosis and intelligent analysis of the causes of urban waterlogging.

[0006] To achieve the above object, the first aspect of the present invention provides an intelligent analysis method for the causes of urban waterlogging, comprising:

[0007] Step 1: Obtain waterlogging data in the target area;

[0008] Step 2: Based on the waterlogging data, determine whether to issue an early warning for the water depth of the waterlogging point; if yes, issue an early warning message and obtain rainfall data; if no, continue monitoring and judgment;

[0009] Step 3: Analyze the causes of waterlogging based on waterlogging data and rainfall data.

[0010] Preferably, the step of obtaining waterlogging data of a target area includes:

[0011] The waterlogging data of the target area is collected in real time through data acquisition equipment; the target area refers to the waterlogging area to be monitored; the waterlogging data include: water depth at the waterlogging point, rainfall information, liquid level / flow of the rainwater pipe network, liquid level / flow of the main pipe, liquid level / flow of the outlet, river water level and operating status of the pump station.

[0012] It should be noted that accurate rainfall information can be obtained by deploying rainfall monitoring stations near water accumulation points or accessing the kilometer-level grid real-time rainfall data of the meteorological department; the rainfall information includes: rainfall amount, rainfall intensity, rainfall time series, etc.

[0013] Operation status monitoring points are set up in all rainwater pumping stations to monitor the liquid level in the pump station front pool, pump start and stop status, fault conditions, etc., to ensure that the operating status of the pump station can be grasped in a timely manner.

[0014] Preferably, judging whether to issue an early warning of the water depth at a waterlogging point based on waterlogging data includes:

[0015] Extract the water depth of the waterlogging point in the real-time waterlogging data;

[0016] Determine whether the water depth is greater than the preset water depth threshold; if so, the water depth monitoring equipment installed at the water accumulation point will issue a warning message; otherwise, continue to monitor and judge.

[0017] It should be noted that the preset water accumulation depth threshold is set by experts in this field based on actual urban waterlogging requirements.

[0018] Preferably, the obtaining of rainfall data comprises:

[0019] Get the start time of rainfall;

[0020] Get the end time of rainfall;

[0021] Obtain rainfall period data; wherein the period data includes: maximum hourly rainfall during the rainfall period, maximum 3-hour rainfall and cumulative rainfall during the rainfall period.

[0022] Preferably, the step of obtaining the start time of rainfall includes:

[0023] S1: When the water depth monitoring equipment at the water accumulation point issues a warning message, the time when the warning message is generated is marked as the monitoring alarm time t0; the historical rainfall monitoring data before time t0 is extracted from the rainfall station closest to the water accumulation point;

[0024] S2: record the nth hour before the monitoring alarm time t0 as t0-n, traverse the rainfall monitoring data from t0-n to t0 in chronological order, and find the first collection time of rainfall data greater than Vmin; where Vmin represents the minimum resolution of rainfall monitoring;

[0025] S3: If no rainfall is found, the subsequent rainfall start time judgment is stopped, that is, if no significant rainfall occurs in the previous n hours, the water accumulation point alarm is a false alarm, and the current alarm is no longer tracked for rainfall events;

[0026] S4: If the first rainfall data greater than Vmin is found, the data collection time is obtained and marked as the start time ts of the rainfall;

[0027] S5: Taking time ts as the starting point, traverse the rainfall monitoring data from time ts to the previous n hours again, and update the new rainfall start time using the same method as S2-S4; repeat this process until no rainfall data greater than Vmin is found, then stop judging and output the start time ts of this rainfall. If the output result is empty, it means that no rainfall occurred before the monitoring alarm was generated at time t0, then stop the dynamic tracking of the rainfall session.

[0028] It should be noted that the value of n can be determined according to the area of ​​the drainage unit, and is usually taken as the drainage time of the drainage unit (for example, for a smaller drainage unit, n can be 1 hour; for a larger drainage unit, n can be 2 hours or longer).

[0029] Preferably, obtaining the end time of rainfall includes:

[0030] A1: Record the time after the monitoring alarm time t0 as t0+1, traverse the rainfall data from t0 to t0+1 in chronological order, and find the last rainfall data greater than Vmin;

[0031] A2: If the last rainfall data greater than Vmin is found, the data collection time is obtained and marked as the end time te of the rainfall;

[0032] A3: If it cannot be found, then record t0+1 as the end time te of the rainfall;

[0033] A4: Traverse the rainfall monitoring data from time te to the next hour, find the last rainfall data greater than Vmin, obtain the data collection time, and update it to the new rainfall end time te; repeat this step until no rainfall data greater than Vmin is found for n consecutive hours starting from the rainfall end time te, then stop judging and output the end time te of this rainfall. If the output result is empty, it means that no rainfall has occurred after the monitoring alarm is generated at time t0, then stop the dynamic tracking of the rainfall session.

[0034] Preferably, the rainfall period data obtained includes: the maximum hourly rainfall in the rainfall period, the maximum 3-hour rainfall and the accumulated rainfall in the rainfall period;

[0035] Obtaining the maximum hourly rainfall during the rainfall period:

[0036] According to the start time ts and end time te of the rainfall period, the rainfall monitoring data in the period is obtained; the cumulative rainfall in each 1-hour time interval is calculated by using a sliding time window, and the rainfall in all 1-hour time intervals is compared, and the maximum value is taken as the maximum hourly rainfall Ih;

[0037] Maximum 3-hour rainfall:

[0038] If the rainfall duration (te-ts) is greater than 3 hours, the monitoring data of the rainfall station in the rainfall period is obtained according to the rainfall start time ts and the rainfall end time te of the rainfall period. The rainfall at each 3-hour time interval is calculated using a sliding time window in the same way as the maximum hourly rainfall, and the maximum hourly rainfall I3h is obtained by comparison.

[0039] If the rainfall duration (te-ts) is less than 2.5 hours, the maximum 3-hour rainfall I3h is not calculated; if the rainfall duration is 2.5 hours ≤ (te-ts) < 3 hours, the accumulated rainfall is directly used as the maximum 3-hour rainfall I3h;

[0040] Obtaining the accumulated rainfall during the rainy period:

[0041] Obtain the rainfall monitoring data within the rainfall period between the rainfall start time ts and the rainfall end time te, accumulate the rainfall Vi of all sampling points, and obtain the cumulative rainfall V; where i is the number of sampling points within the rainfall period.

[0042] Preferably, the waterlogging cause analysis based on waterlogging data and rainfall data includes:

[0043] Analyze waterlogging based on preset waterlogging causes; among them, the preset waterlogging causes include: insufficient water collection capacity or blockage of rainwater inlets, sewage mixing in rainwater pipe networks or high water levels during dry days, overflow caused by high water levels in sewage pipe networks during dry days and inflow and infiltration during rainy days, blockage of the downstream drainage pipe network of waterlogging points, abnormal start-up or insufficient drainage capacity of pump stations, backwater of high water levels in river water systems, insufficient design capacity of drainage pipe networks, and heavy rainfall intensity.

[0044] Preferably, the analysis of waterlogging based on preset waterlogging causes includes:

[0045] Analysis of insufficient water collection capacity or blockage of rainwater inlets:

[0046] Extract the start time ts and end time te of rainfall; after the rainfall ends, query the time-series data of water depth monitoring at the waterlogging point within the rainfall period (ts~te) to obtain the start waterlogging moment t0; where the start waterlogging moment refers to the moment when the water depth first rises to 0.15.

[0047] In the time-series data of low-point liquid level monitoring of the local rainwater pipe network, according to the start waterlogging moment t0, interpolate to obtain the liquid level monitoring value h0 corresponding to the start waterlogging moment t0 within the rainfall period (ts~te); in the time-liquid level monitoring data, find the moments tf and tb before and after t0 and the corresponding monitored liquid levels hf and hb, and obtain h0 = (hb - hf) / (tb - tf)*(t0 - tf)+hf through linear interpolation.

[0048] Judge whether the monitored liquid level h0 reaches the well depth d of the inspection well where the equipment is located or reaches the maximum monitored range, that is, hmin < h0 < d - α·FS, where hmin represents the minimum resolution of the liquid level monitoring equipment, α represents the full-scale error of the equipment, and FS represents the full scale of the equipment. If the condition is met, it means that the surface waterlogging is not caused by the full-load operation of the pipe network and inspection well, and the waterlogging cause is: insufficient water collection capacity of the rainwater inlet or possible blockage.

[0049] Analysis of sewage mixing in rainwater pipe networks or high water levels during dry days:

[0050] After the rain is over, check whether there is a diagnosis result of sewage mixing disease at the low-point liquid level monitoring point of the local rainwater pipe network, and whether the characteristic time of the most recent disease diagnosis is within 30 days from the end of the rain; if so, obtain the dry day average liquid level have of the most recent sewage mixing disease diagnosis result; query the bottom elevation Hb of the inspection well where the low-point liquid level monitoring point of the local rainwater pipe network is located, and according to the pipe point-pipe section connection relationship of the rainwater pipe network, query the downstream pipe section of the inspection well where the liquid level monitoring point is located, as well as the upstream pipe bottom elevation S_H and cross-sectional size D of the downstream pipe section; continue to judge whether the dry day average liquid level reaches the high water level operation judgment condition have≥[0.4*D+(S_H-Hb)], if the condition is met, the cause of the water accumulation at the water accumulation point is: there is sewage misconnection and mixing upstream of the local rainwater pipe network, the average daily liquid level on dry days is have, the liquid level is high, and the flow capacity of rainwater on rainy days is affected;

[0051] After the rainfall ends, if the diagnosis result of sewage misconnection and mixing disease cannot be found 30 days before the rainfall end time te, then according to the dry period judgment principle: the non-rainfall period after 72 consecutive hours of no rainfall, judge whether the rainfall start time ts is a dry period. If it is a dry period, take the liquid level monitoring data hs corresponding to the rainfall start time ts in the time series data of the low point liquid level monitoring of the local rainwater pipe network. Specifically: in the time-liquid level monitoring data set, find the time before and after ts and the corresponding monitoring liquid level, and obtain hs by linear interpolation, and then judge whether the liquid level hs reaches the judgment condition of high water level operation hs≥[0.4*D+(S_H-Hb)], if the condition is met, the cause of the water accumulation at the water accumulation point is: the dry monitoring liquid level of the local rainwater pipe network is hsm, the liquid level is relatively high, affecting the flow capacity of rainwater on rainy days;

[0052] Analysis of overflow caused by high water level in the sewage pipe network during dry days and inflow and infiltration during rainy days:

[0053] In the time series data of the low point liquid level monitoring of the local sewage pipe network, according to the time t0 of the beginning of water accumulation, the liquid level monitoring value hws0 corresponding to the time t0 of the beginning of water accumulation is obtained by interpolation during the rainfall period;

[0054] In the time-liquid level monitoring data, find the time tf and tb before and after t0 and the corresponding monitoring liquid levels hwsf and hwsb, and linearly interpolate to obtain hws0 = (hwsb-hwsf) / (tb-tf)*(t0-tf)+hwsf;

[0055] Determine whether the monitoring liquid level hws0 reaches the depth deepws of the inspection well where the equipment is located or reaches the maximum monitoring range, that is, hws0 ≥ (deepws-α*FS), where α represents the full-scale error of the equipment and FS represents the full-scale range of the equipment;

[0056] If the conditions are met, the local sewage pipe network low-point liquid level monitoring point is further queried to see if there is a diagnosis result of rainwater inflow and infiltration at the end of the previous natural month. If so, the cause of the waterlogging is: there is a serious problem of rainwater inflow and infiltration on rainy days, resulting in sewage overflow;

[0057] According to the diagnosis results of rainwater inflow and infiltration diseases at the low-point liquid level monitoring point of the local sewage pipe network at the end of the previous natural month, the average monitoring liquid level hwsave of all dry days in one month is obtained, and the bottom elevation Hwsb of the inspection well where the low-point liquid level monitoring point of the local sewage pipe network is located is queried. According to the pipe point-pipe section connection relationship of the sewage pipe network, the downstream pipe section of the inspection well where the liquid level monitoring point is located, as well as the upstream pipe bottom elevation S_Hws and cross-sectional size Dws of the downstream pipe section are queried; and the judgment condition hwsave≥[Camax*Dws+(S_Hws-Hwsb)] of the dry day is further judged to determine whether the average liquid level on the dry day reaches the high water level operation, where Camax is the maximum design fullness of the sewage pipe specified in the "Outdoor Drainage Design Standard"; if the judgment condition is met, the cause of water accumulation is further output as follows: the sewage is running at a high water level on dry days, the average liquid level is hwsave, and there is a serious rainwater inflow and infiltration problem on rainy days, resulting in sewage overflow;

[0058] Analysis of clogging of drainage pipe network downstream of water accumulation point:

[0059] After the rainfall is over, determine whether there are any blockage diagnosis results at the liquid level or flow monitoring points of the local rainwater pipe network and sewage pipe network, and whether the characteristic time of the most recent disease diagnosis is within 30 days from the end time of the rainfall te. If so, the cause of water accumulation at the water accumulation point is: the downstream pipe network may be blocked, affecting the flow capacity of rainwater on rainy days.

[0060] It should be noted that time-level monitoring data refers to the liquid level change information collected and recorded by a liquid level meter (such as a water level sensor, a pressure sensor, etc.) within a specific time interval, and is usually stored in the form of a time series.

[0061] Preferably, the analyzing of waterlogging based on a preset cause of waterlogging further includes:

[0062] Analysis of abnormal pump station start-up and insufficient drainage capacity:

[0063] After the rainfall ends, query the water depth monitoring data of the waterlogging point during the rainfall period to obtain the time t0 when the waterlogging starts; based on the time t0 when the waterlogging starts, determine whether the on / off status of the pump station at the corresponding time can be queried within the subsequent Δt; where Δt is the collection period of the pump station operation status;

[0064] If it can be queried, count the number M of pumps with the status of "closed" and "fault" at the corresponding time. If M≥2, the cause of waterlogging is: abnormal start of the pumping station and insufficient drainage capacity;

[0065] Analysis of the high water level backwater of the river water system:

[0066] Based on the waterlogging point and the local pipe network liquid level monitoring points, according to the rainwater pipe network topology relationship, it can be traced back to the corresponding outfall, and there is no rainwater pumping station in the middle. If there is a liquid level or flow monitoring device on the main pipe near the outfall, or there is a river water level gauge device near the outfall, the influence of the high water level backwater downstream can be analyzed and judged;

[0067] If there is no outfall downstream, or there is a pumping station in the middle, or there is no corresponding river water level gauge and no corresponding main pipe liquid level or flow monitoring device, it is impossible to judge the high water level backwater of the river water system, and there is no need to perform subsequent calculations and judgments;

[0068] Starting from the lowest pipe point of the local rainwater pipe network at the waterlogging point, according to the connection relationship between pipe segments and pipe points, find all pipe segments from the downstream of this lowest pipe point to the outfall, and obtain the upstream pipe bottom elevation S_Hj, downstream pipe bottom elevation E_Hj and cross-sectional dimension Dj of each pipe segment in the pipe segment data table; where j represents the jth pipe segment;

[0069] After the rainfall ends, query the water depth monitoring data at the waterlogging point during the rainfall period to obtain the start waterlogging time t0; search for the river water level gauge in the river or lake water system downstream of the waterlogging point, and obtain the river water level value L0 at the start waterlogging time t0 according to the linear interpolation method in the river water level monitoring data; where L0 is the absolute elevation of the river water level at the water surface; judge whether the first pipe segment downstream of the lowest pipe point of the local rainwater pipe network at the waterlogging point satisfies: L0≥(S_Hj+Dj). If it is satisfied, further count the number N of pipe segments that satisfy L0<S_Hj or L0<E_Hj among all pipe segments from the downstream of the lowest pipe point to the outfall. If N = 0, the cause of waterlogging at the waterlogging point is: affected by the high water level backwater of the downstream river, the drainage is not smooth;

[0070] If there is no river water level gauge near the outfall downstream of the waterlogging point, but there is a corresponding liquid level gauge or flowmeter on the downstream main pipe, then according to the start waterlogging time t0, obtain the liquid level value h0 at time t0 according to the linear interpolation method in the liquid level monitoring data, and calculate the absolute water level corresponding to this liquid level (h0+H) according to the inner bottom elevation H of the pipe point; judge whether the first pipe segment downstream of the lowest pipe point of the local rainwater pipe network at the waterlogging point satisfies: (h0+H)≥(S_Hj+Dj). If it is satisfied, further count the number N of pipe segments that satisfy (h0+H)<S_Hj or (h0+H)<E_Hj among all pipe segments from the downstream of the lowest pipe point to the outfall. If N = 0, the cause of waterlogging at the waterlogging point is: affected by the high water level backwater downstream, the drainage is not smooth;

[0071] Analysis of insufficient design capacity of drainage pipe network:

[0072] Extract the start time ts and end time te of rainfall, the maximum hourly rainfall Ih, the maximum 3-hour rainfall I3h, and the cumulative rainfall Vi during the rainfall period;

[0073] According to the rainstorm intensity formula compiled by the local meteorological department, inversely deduce the rainstorm recurrence period P of this rainfall event:

[0074] i = Ih / 60;

[0075] q = 167f;

[0076] ClgP = [(q(t + b)^n) / 167A1] - 1;

[0077] Among them, the rainfall duration t is taken as 60 min; the parameters A1, C, b, and n are obtained according to the local compiled rainstorm intensity formula, f is the rainfall intensity, with the unit of mm / min; according to the maximum hourly rainfall Ih and the maximum 3-hour rainfall I3h of the rainfall event, calculate the corresponding rainstorm recurrence periods Ph and P3h respectively, and take the larger value of the two as the rainstorm recurrence period P of this rainfall event, P = max(Ph, P3h);

[0078] According to the urban type where the waterlogging point is located, obtain the design recurrence period Ps of the local drainage pipe network in accordance with the provisions of the "Outdoor Drainage Design Standard". If P < Ps and the above analyses are not valid, then the cause of waterlogging is: insufficient design capacity of the local drainage pipe network at the waterlogging point;

[0079] Analysis of large rainfall intensity:

[0080] Based on the rainstorm recurrence period Pi of rainfall and the design recurrence period Ps of the local drainage pipe network at the waterlogging point obtained, if Pi ≥ Ps, then the cause of waterlogging is: the maximum hourly rainfall reaches Ih mm, the maximum 3-hour rainfall reaches I3h mm, and the short-term rainfall intensity is large.

[0081] Compared with the prior art, the beneficial effects of the present invention are:

[0082] 1. The present invention obtains the waterlogging data of the target area; judges whether to give an early warning of the waterlogging depth at the waterlogging point based on the waterlogging data; if so, issues an early warning message and obtains rainfall data; if not, continues to monitor and judge; conducts an analysis of the causes of waterlogging and ponding based on the waterlogging data and rainfall data, and solves the technical problems that in the prior art, a large number of ground and underground Internet of Things monitoring devices have been built in the construction of smart drainage projects in various places, and three-dimensional monitoring of rainfall, pipe network conditions, surface ponding, river water levels, etc. has been carried out, but most projects have insufficient big data analysis capabilities based on three-dimensional monitoring and lack technical means for diagnosing the operation of pipe network facilities and intelligently analyzing the causes of waterlogging and ponding.

[0083] 2. The present invention uses an intelligent analysis method for 8 typical causes of urban waterlogging, which can timely and dynamically track rainfall events when an alarm is sounded at the waterlogging point, with strong timeliness; the 8 causes of urban waterlogging include drainage network blockage, insufficient or blocked rainwater inlet water collection capacity, rainwater and sewage mixing, rainwater inflow and infiltration, high water level operation, sewage overflow, insufficient design capacity of the drainage network and other network operation defects, as well as drainage facility operation failures and downstream drainage obstacles, as well as natural factors such as abnormal operation of pump stations and high water level support in rivers, as well as natural factors such as high rainfall intensity, basically covering all factors that cause urban waterlogging, with a comprehensive analysis and strong applicability; as a big data analysis algorithm that integrates static data and dynamic monitoring data of drainage facilities, this method can be integrated into the smart drainage system platform to intelligently analyze the causes of urban waterlogging, provide guidance for manual offline investigation and analysis, and improve the big data analysis level of drainage monitoring. BRIEF DESCRIPTION OF THE DRAWINGS

[0084] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0085] Figure 1 A schematic diagram of the method steps of an embodiment of the present invention;

[0086] Figure 2 Schematic diagram of the steps of a method for obtaining the end time of rainfall according to an embodiment of the present invention. DETAILED DESCRIPTION

[0087] The technical scheme of the present invention will be clearly and completely described below in conjunction with the embodiments. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0088] See also Figure 1 The first embodiment of the present invention provides an intelligent analysis method for the causes of urban waterlogging, including:

[0089] Step 1: Obtain waterlogging data in the target area;

[0090] Step 2: Based on the waterlogging data, determine whether to issue an early warning for the water depth of the waterlogging point; if yes, issue an early warning message and obtain rainfall data; if no, continue monitoring and judgment;

[0091] Step 3: Analyze the causes of waterlogging based on waterlogging data and rainfall data.

[0092] Obtain waterlogging data for the target area, including:

[0093] The waterlogging data of the target area is collected in real time through data acquisition equipment; the target area refers to the waterlogging area to be monitored; the waterlogging data include: water depth at the waterlogging point, rainfall information, liquid level / flow of the rainwater pipe network, liquid level / flow of the main pipe, liquid level / flow of the outlet, river water level and operating status of the pump station.

[0094] Determine whether to issue an early warning of the water depth at the waterlogging point based on waterlogging data, including:

[0095] Extract the water depth of the waterlogging point in the real-time waterlogging data;

[0096] Determine whether the water depth is greater than the preset water depth threshold; if so, the water depth monitoring equipment installed at the water accumulation point will issue a warning message; otherwise, continue to monitor and judge.

[0097] Get rainfall data, including:

[0098] Get the start time of rainfall;

[0099] Get the end time of rainfall;

[0100] Obtain rainfall period data; wherein the period data includes: maximum hourly rainfall during the rainfall period, maximum 3-hour rainfall and cumulative rainfall during the rainfall period.

[0101] Get the start time of rainfall, including:

[0102] S1: When the water depth monitoring equipment at the water accumulation point issues a warning message, the time when the warning message is generated is marked as the monitoring alarm time t0; the historical rainfall monitoring data before time t0 is extracted from the rainfall station closest to the water accumulation point;

[0103] S2: record the nth hour before the monitoring alarm time t0 as t0-n, traverse the rainfall monitoring data from t0-n to t0 in chronological order, and find the first collection time of rainfall data greater than Vmin; where Vmin represents the minimum resolution of rainfall monitoring;

[0104] S3: If no rainfall is found, the subsequent rainfall start time judgment is stopped, that is, if no significant rainfall occurs in the previous n hours, the water accumulation point alarm is a false alarm, and the alarm is no longer tracked for rainfall events;

[0105] S4: If the first rainfall data greater than Vmin is found, the data collection time is obtained and marked as the start time ts of the rainfall;

[0106] S5: Taking time ts as the starting point, traverse the rainfall monitoring data from time ts to the previous n hours again, and update the new rainfall start time using the same method as S2-S4; repeat this process until no rainfall data greater than Vmin is found, then stop judging and output the start time ts of this rainfall. If the output result is empty, it means that no rainfall occurred before the monitoring alarm was generated at time t0, then stop the dynamic tracking of the rainfall session.

[0107] See also Figure 2 , get the end time of rainfall, including:

[0108] A1: Record the time after the monitoring alarm time t0 as t0+1, traverse the rainfall data from t0 to t0+1 in chronological order, and find the last rainfall data greater than Vmin;

[0109] A2: If the last rainfall data greater than Vmin is found, the data collection time is obtained and marked as the end time te of the rainfall;

[0110] A3: If it cannot be found, then record t0+1 as the end time te of the rainfall;

[0111] A4: Traverse the rainfall monitoring data from time te to the next hour, find the last rainfall data greater than Vmin, obtain the data collection time, and update it to the new rainfall end time te; repeat this step until no rainfall data greater than Vmin is found for n consecutive hours starting from the rainfall end time te, then stop judging and output the end time te of this rainfall. If the output result is empty, it means that no rainfall has occurred after the monitoring alarm is generated at time t0, then stop the dynamic tracking of the rainfall session.

[0112] Obtain rainfall period data, including: maximum hourly rainfall during the rainfall period, maximum 3-hour rainfall, and cumulative rainfall during the rainfall period;

[0113] Obtaining the maximum hourly rainfall during the rainfall period:

[0114] According to the start time ts and end time te of the rainfall period, the rainfall monitoring data in the period is obtained; the cumulative rainfall in each 1-hour time interval is calculated by using a sliding time window, and the rainfall in all 1-hour time intervals is compared, and the maximum value is taken as the maximum hourly rainfall Ih;

[0115] Maximum 3-hour rainfall:

[0116] If the rainfall duration (te-ts) is greater than 3 hours, the monitoring data of the rainfall station in the rainfall period is obtained according to the rainfall start time ts and the rainfall end time te of the rainfall period. The rainfall at each 3-hour time interval is calculated using a sliding time window in the same way as the maximum hourly rainfall, and the maximum hourly rainfall I3h is obtained by comparison.

[0117] If the rainfall duration (te-ts) is less than 2.5 hours, the maximum 3-hour rainfall I3h is not calculated; if the rainfall duration is 2.5 hours ≤ (te-ts) < 3 hours, the accumulated rainfall is directly used as the maximum 3-hour rainfall I3h;

[0118] Obtaining the accumulated rainfall during the rainy period:

[0119] Obtain the rainfall monitoring data within the rainfall period between the rainfall start time ts and the rainfall end time te, accumulate the rainfall Vi of all sampling points, and obtain the cumulative rainfall V; where i is the number of sampling points within the rainfall period.

[0120] Analysis of the causes of waterlogging based on waterlogging data and rainfall data, including:

[0121] The waterlogging is analyzed based on the preset causes of waterlogging; among them, the preset causes of waterlogging include: insufficient water collection capacity or siltation of rainwater inlets, sewage mixing in the rainwater pipe network or high water level operation in dry days, overflow caused by high water level in the sewage pipe network in dry days and inflow and infiltration in rainy days, siltation of the drainage pipe network downstream of the waterlogging point, abnormal opening of the pump station or insufficient drainage capacity, high water level support of the river system, insufficient design capacity of the drainage pipe network and high rainfall intensity.

[0122] Analyze waterlogging based on pre-determined causes of waterlogging, including:

[0123] Analysis of insufficient water collection capacity or siltation of rainwater inlets:

[0124] Extract the start time ts and end time te of the rainfall; after the rainfall ends, query the time series data of water depth monitoring at the waterlogging point within the rainfall period (ts~te) to obtain the start time t0 of waterlogging; where the start time of waterlogging refers to the time when the waterlogging depth first rises to 0.15;

[0125] In the time series data of the low-point liquid level monitoring of the local rainwater pipe network, according to the time of water accumulation t0, the liquid level monitoring value h0 corresponding to the time of water accumulation t0 is interpolated in the rainfall period (ts~te); in the time-liquid level monitoring data, the time before and after t0 tf, tb and the corresponding monitoring liquid levels hf, hb are found, and h0 = (hb-hf) / (tb-tf)*(t0-tf)+hf is obtained by linear interpolation;

[0126] Judge whether the monitored liquid level h0 reaches the well depth d of the inspection well where the equipment is located or reaches the maximum monitoring range, that is, hmin < h0 < d - α·FS, where hmin represents the minimum resolution of the liquid level monitoring equipment, α represents the full-scale error of the equipment, and FS represents the full scale of the equipment. If the condition is met, it indicates that the ground water accumulation is not caused by the full-load operation of the pipe network and inspection wells. The reasons for the water accumulation are: insufficient water collection capacity of the rainwater inlets or possible blockage;

[0127] Analysis of sewage misconnection or high water level operation in dry weather in the rainwater pipe network:

[0128] After the rainfall ends, query whether there is a diagnosis result of sewage misconnection disease at the low-point liquid level monitoring point of the local rainwater pipe network, and the characteristic time of the most recent disease diagnosis is within 30 days from the end time of the rainfall; if so, obtain the average dry-weather liquid level have of the most recent sewage misconnection disease diagnosis result; query the bottom elevation Hb of the inspection well where the low-point liquid level monitoring point of the local rainwater pipe network is located, and according to the pipe point - pipe segment connection relationship of the rainwater pipe network, query the downstream pipe segment of the inspection well where the liquid level monitoring point is located, and the upstream pipe bottom elevation S_H and cross-sectional dimension D of this downstream pipe segment; continue to judge whether the average dry-weather liquid level reaches the judgment condition for high water level operation have ≥ [0.4*D + (S_H - Hb)]. If the condition is met, the reason for the water accumulation at this water accumulation point is: there is sewage misconnection in the upstream of the local rainwater pipe network, the average daily dry-weather liquid level is have, and the liquid level is relatively high, affecting the rainwater flow capacity during rainy days;

[0129] After the rainfall ends, if no diagnosis result of sewage misconnection disease can be queried 30 days before the rainfall end time te, then according to the dry-weather period judgment principle: the non-rainfall period after 72 consecutive hours of no rainfall, judge whether the rainfall start time ts is a dry-weather period. If it is a dry-weather period, in the time series data of the low-point liquid level monitoring of the local rainwater pipe network, take the liquid level monitoring data hs corresponding to the rainfall start time ts. Specifically: in the time - liquid level monitoring data set, find the moments before and after ts and the corresponding monitored liquid levels, and linearly interpolate to obtain hs accordingly. Then judge whether the liquid level hs reaches the judgment condition for high water level operation hs ≥ [0.4*D + (S_H - Hb)]. If the condition is met, the reason for the water accumulation at this water accumulation point is: the dry-weather monitored liquid level of the local rainwater pipe network is hsm, and the liquid level is relatively high, affecting the rainwater flow capacity during rainy days;

[0130] Analysis of sewage pipe network high water level in dry weather and over-infiltration during rainy days resulting in overflow:

[0131] In the time series data of the low-point liquid level monitoring of the local sewage pipe network, according to the start water accumulation moment t0, interpolate to obtain the liquid level monitoring value hws0 corresponding to the start water accumulation moment t0 during the rainfall period;

[0132] In the time-liquid level monitoring data, find the time tf and tb before and after t0 and the corresponding monitoring liquid levels hwsf and hwsb, and linearly interpolate to obtain hws0 = (hwsb-hwsf) / (tb-tf)*(t0-tf)+hwsf;

[0133] Determine whether the monitoring liquid level hws0 reaches the depth deepws of the inspection well where the equipment is located or reaches the maximum monitoring range, that is, hws0 ≥ (deepws-α*FS), where α represents the full-scale error of the equipment and FS represents the full-scale range of the equipment;

[0134] If the conditions are met, the local sewage pipe network low-point liquid level monitoring point is further queried to see if there is a diagnosis result of rainwater inflow and infiltration at the end of the previous natural month. If so, the cause of the waterlogging is: there is a serious problem of rainwater inflow and infiltration on rainy days, resulting in sewage overflow;

[0135] According to the diagnosis results of rainwater inflow and infiltration diseases at the low-point liquid level monitoring point of the local sewage pipe network at the end of the previous natural month, the average monitoring liquid level hwsave of all dry days in one month is obtained; the bottom elevation Hwsb of the inspection well where the low-point liquid level monitoring point of the local sewage pipe network is located is queried, and according to the pipe point-pipe section connection relationship of the sewage pipe network, the downstream pipe section of the inspection well where the liquid level monitoring point is located, as well as the upstream pipe bottom elevation S_Hws and cross-sectional size Dws of the downstream pipe section are queried; and the judgment condition hwsave≥[Camax*Dws+(S_Hws-Hwsb)] of the dry day is further judged to determine whether the average liquid level on the dry day reaches the high water level operation, where Camax is the maximum design fullness of the sewage pipe specified in the "Outdoor Drainage Design Standard"; if the judgment condition is met, the cause of water accumulation is further output as follows: the sewage is running at a high water level on dry days, the average liquid level is hwsave, and there is a serious rainwater inflow and infiltration problem on rainy days, resulting in sewage overflow;

[0136] Analysis of clogging of drainage pipe network downstream of water accumulation point:

[0137] After the rainfall is over, determine whether there are any blockage diagnosis results at the liquid level or flow monitoring points of the local rainwater pipe network and sewage pipe network, and whether the characteristic time of the most recent disease diagnosis is within 30 days from the end time of the rainfall te. If so, the cause of water accumulation at the water accumulation point is: the downstream pipe network may be blocked, affecting the flow capacity of rainwater on rainy days.

[0138] Analysis of waterlogging based on pre-determined causes of waterlogging, including:

[0139] Analysis of abnormal pump station start-up and insufficient drainage capacity:

[0140] After the rainfall ends, query the water depth monitoring data of the waterlogging point during the rainfall period to obtain the starting waterlogging moment t0; according to the starting waterlogging moment t0, judge whether the opening and closing status of the pump station at the corresponding moment can be queried within the subsequent Δt; where Δt is the acquisition period of the pump station operation status.

[0141] If it can be queried, count the number M of pumps with the status of "closed" and "fault" at the corresponding moment. If M≥2, the cause of waterlogging is: abnormal pump station opening and insufficient drainage capacity.

[0142] Analysis of the high water level backwater of the river channel water system:

[0143] According to the waterlogging point and the local pipe network liquid level monitoring points, and according to the rainwater pipe network topology relationship, it can be traced back to the corresponding drainage outlet, and there is no rainwater pump station in the middle. If there is a liquid level or flow monitoring device on the main pipe near the drainage outlet, or there is a river water level gauge device near the drainage outlet, the influence of the high water level backwater in the downstream can be analyzed and judged.

[0144] If there is no drainage outlet downstream, or there is a pump station in the middle, or there is no corresponding river water level gauge and no corresponding main pipe liquid level or flow monitoring device, it is impossible to judge the high water level backwater of the river channel water system, and there is no need to perform subsequent calculations and judgments.

[0145] Taking the lowest pipe point of the local rainwater pipe network at the waterlogging point as the starting point, according to the connection relationship between the pipe section and the pipe point, find all the pipe sections from the downstream of this lowest pipe point to the drainage outlet, and obtain the upstream pipe bottom elevation S_Hj, downstream pipe bottom elevation E_Hj and cross-sectional dimension Dj of each pipe section in the pipe section data table; where j represents the jth pipe section.

[0146] After the rainfall ends, query the water depth monitoring data of the waterlogging point during the rainfall period to obtain the starting waterlogging moment t0; find the water level gauge of the downstream river or lake water system of the waterlogging point, and obtain the river water level value L0 at the starting waterlogging moment t0 according to the linear interpolation method in the river water level monitoring data; where L0 is the absolute elevation of the river water level at the water surface; judge whether the first pipe section downstream of the lowest pipe point of the local rainwater pipe network at the waterlogging point satisfies: L0≥(S_Hj+Dj). If it is satisfied, further count the number N of pipe sections that satisfy L0<S_Hj or L0<E_Hj among all the pipe sections from the downstream of the lowest pipe point to the drainage outlet. If N = 0, the cause of waterlogging at the waterlogging point is: affected by the high water level backwater of the downstream river, the drainage is not smooth.

[0147] If there is no river water level gauge near the outlet downstream of the waterlogging point, but there is a corresponding liquid level gauge or flowmeter in the downstream main pipe, then according to the start time of waterlogging t0, in the liquid level monitoring data, obtain the liquid level value h0 at time t0 by linear interpolation method. According to the inner bottom elevation H of the pipe point, calculate the absolute water level corresponding to this liquid level (h0 + H); judge whether the first pipe segment downstream of the lowest pipe point of the local rainwater pipe network at the waterlogging point satisfies: (h0 + H) ≥ (S_Hj + Dj). If it is satisfied, then further count the number N of pipe segments that satisfy (h0 + H) < S_Hj or (h0 + H) < E_Hj among all pipe segments from the lowest pipe point downstream to the outlet. If N = 0, the reason for waterlogging at the waterlogging point is: affected by the high water level in the downstream, the drainage is not smooth.

[0148] Analysis of insufficient design capacity of the drainage pipe network:

[0149] Extract the start time ts and end time te of the rainfall, the maximum hourly rainfall Ih, the maximum 3-hour rainfall I3h, and the cumulative rainfall Vi during the rainfall period;

[0150] According to the rainstorm intensity formula compiled by the local meteorological department, inversely deduce the rainstorm recurrence period P of this rainfall:

[0151] i = Ih / 60;

[0152] q = 167f;

[0153] ClgP = [(q(t + b)^n) / 167A1] - 1;

[0154] Among them, the rainfall duration t takes 60 min; the parameters A1, C, b, and n are obtained according to the locally compiled design rainstorm intensity formula, f is the rainfall intensity, with the unit of mm / min; according to the maximum hourly rainfall Ih and the maximum 3-hour rainfall I3h of the rainfall event, calculate the corresponding rainstorm recurrence periods Ph and P3h respectively, and take the larger value of the two as the rainstorm recurrence period P of this rainfall event, P = max(Ph, P3h);

[0155] According to the type of urban area where the waterlogging point is located, obtain the design recurrence period Ps of the local drainage pipe network in accordance with the "Outdoor Drainage Design Standard". If P < Ps and none of the above analyses are valid, the reason for waterlogging is: the design capacity of the local drainage pipe network at the waterlogging point is insufficient;

[0156] Analysis of large rainfall intensity:

[0157] Based on the rainstorm recurrence period Pi of the rainfall and the design recurrence period Ps of the local drainage pipe network at the waterlogging point obtained, if Pi ≥ Ps, the reason for waterlogging is: the maximum hourly rainfall reaches Ih mm, the maximum 3-hour rainfall reaches I3h mm, and the short-term rainfall intensity is large.

[0158] For example, if a waterlogging point in a city (denoted as point A) has a waterlogging alarm, the system will intelligently analyze the cause of the waterlogging at the waterlogging point according to the above method. The details are as follows:

[0159] Target area: A low-lying area (point A) on a main road in the central area of ​​a city, which is prone to waterlogging.

[0160] Monitoring equipment:

[0161] Water depth monitoring equipment: installed at point A to monitor the depth of accumulated water in real time.

[0162] Rainfall monitoring station: The nearest rainfall station to point A is located 500 meters away, with a sampling frequency of once every 5 minutes.

[0163] Liquid level monitoring equipment: Liquid level monitoring equipment is installed at the low points of the rainwater pipe network, the low points of the sewage pipe network, the main pipes, the outlets and other locations near point A, with a sampling frequency of once every 10 minutes.

[0164] Pump station operation status monitoring: Operation status monitoring equipment is installed at the rainwater pump station downstream of point A to monitor the liquid level in the pump station forebay, pump start and stop status, fault conditions, etc. in real time.

[0165] Step 1: Obtain waterlogging data in the target area;

[0166] 1. Real-time collection of waterlogging data:

[0167] Water depth at the water accumulation point: The water depth monitoring equipment collects the water depth at point A in real time.

[0168] Rainfall information: Obtain information such as rainfall amount, rainfall intensity, and rainfall time series from the rain gauge station closest to point A.

[0169] Stormwater pipe network liquid level / flow: obtain liquid level data from the low point liquid level monitoring equipment of the stormwater pipe network near point A.

[0170] Main pipe liquid level / flow: Obtain liquid level data from the main pipe liquid level monitoring device downstream of point A.

[0171] Outlet liquid level / flow: Get the liquid level data from the outlet liquid level monitoring device downstream of point A.

[0172] River water level: Obtain river water level data from the water level gauge in the river near point A.

[0173] Pump station operation status: obtain data such as the pump station forebay liquid level, pump start and stop status, and fault conditions from the rainwater pump station downstream of point A.

[0174] Step 2: Determine whether to issue an early warning for the depth of water at the water point;

[0175] 1. Extract real-time water depth:

[0176] The system extracts the real-time water depth at point A from the water depth monitoring equipment.

[0177] 2. Determine whether it exceeds the preset threshold:

[0178] The preset water depth threshold is 0.15 meters (set according to urban waterlogging requirements).

[0179] Assume that at 14:00, the water depth at point A reaches 0.2 meters, exceeding the preset threshold.

[0180] 3. Issue early warning information:

[0181] The system immediately issues a warning message and records the time when the warning message is generated.

[0182] Step 3: Obtain rainfall data;

[0183] 1. Get the start time ts of rainfall:

[0184] S1: The system extracts the historical rainfall monitoring data before time t0 from the rain gauge station closest to point A.

[0185] S2: Record the time one hour before t0 as t0-1, i.e. 13:00. Traverse the rainfall monitoring data between 13:00 and 14:00 in chronological order, and find the first rainfall data greater than the minimum resolution Vmin (assuming Vmin = 0.1 mm).

[0186] S3: Find out that the rainfall at 13:15 is 0.2 mm, which meets the condition, so mark ts=13:15 as the start time of rainfall.

[0187] 2. Get the end time of rainfall te:

[0188] A1: Record the time after t0 as t0+1, i.e. 15:00. Traverse the rainfall monitoring data between 14:00 and 15:00 in chronological order and find the last rainfall data greater than Vmin.

[0189] A2: The rainfall at 14:45 is found to be 0.15 mm, which meets the condition, so te=14:45 is marked as the end time of the rainfall.

[0190] 3. Get rainfall period data:

[0191] Maximum hourly rainfall Ih: Based on the rainfall monitoring data between 13:15 and 14:45, the cumulative rainfall in each 1-hour time interval is calculated using a sliding time window. Assuming that between 13:30 and 14:30, the maximum hourly rainfall is 10 mm, so Ih = 10 mm / h.

[0192] Maximum 3-hour rainfall I3h: Since the rainfall duration is 1.5 hours (less than 2.5 hours), the accumulated rainfall is directly used as the maximum 3-hour rainfall. Assuming the accumulated rainfall is 15 mm, I3h = 15 mm.

[0193] Cumulative rainfall V: The cumulative rainfall at all sampling points between 13:15 and 14:45 is added up to obtain a cumulative rainfall of 15 mm, so V = 15 mm.

[0194] Step 4: Analyze the causes of waterlogging based on waterlogging data and rainfall data;

[0195] 1. Analysis of insufficient water collection capacity or siltation of rainwater outlets:

[0196] Extract the time t0 when water accumulation starts: In the water depth monitoring data between 13:15 and 14:45, find the time when the water depth first rises to 0.15 meters. Assume that at 14:00, the water depth first reaches 0.15 meters, so t0 = 14:00).

[0197] Get the liquid level h0 corresponding to the time when water accumulation begins: Find the liquid level data around 14:00 in the low-point liquid level monitoring data of the rainwater pipe network near point A. Assuming that the liquid level at 13:50 is 2.5 meters and the liquid level at 14:10 is 2.7 meters, h0 = 2.6m is calculated by linear interpolation.

[0198] Determine whether the liquid level has reached full load operation: Assume that the depth of the inspection well is 3 meters, the full scale error of the equipment is α = 0.1, the full scale FS = 3m, and the minimum resolution is 0.1 meter. The calculation conditions are: 0.1 < 2.6 < 3-0.1 × 3;

[0199] The conditions are met, indicating that the ground waterlogging is not caused by the full-load operation of the pipeline network and inspection wells, but may be caused by insufficient water collection capacity of the rainwater outlet or possible siltation.

[0200] 2. Analysis of the existence of sewage mixing in the rainwater pipe network or high water level operation in dry days:

[0201] Query the diagnosis results of sewage mixing disease: After the rainfall ends (14:45), the system queries whether there are any diagnosis results of sewage mixing disease at the low-point liquid level monitoring point of the rainwater pipe network near point A. Assume that the most recent disease diagnosis time is December 1, 2024, which is within 30 days from the end of the rainfall, and the diagnosis result shows that there is a sewage mixing problem.

[0202] Get the average liquid level on dry days: According to the diagnosis results, the average liquid level in the diseased area on dry days is 2.8 meters.

[0203] Query the geometric parameters of the pipe network: Query the bottom elevation of the inspection well where the low-point liquid level monitoring point of the rainwater pipe network near point A is located. The elevation of the upstream bottom of the downstream pipe section is S_H=1.5m, and the cross-sectional dimension is D=1.0m.

[0204] Determine the high water level operating conditions: Calculate the high water level operating conditions: 2.8 ≥ 0.4 × 1.0 + (1.5-2.0);

[0205] The calculation result is 2.8≥0.9, and the condition is met, indicating that there is sewage misconnection and mixing upstream of the local rainwater pipe network. The average daily liquid level on dry days is 2.8 meters, and the liquid level is relatively high, which affects the flow capacity of rainwater on rainy days.

[0206] 3. Analysis of other causes of waterlogging:

[0207] Abnormal opening of the pump station or insufficient drainage capacity: Between 14:00 and 14:45, the pump station's opening and closing status was checked, and it was found that the pump station was closed from 14:10 to 14:30, and two water pumps failed. Therefore, the cause of the water accumulation was abnormal opening of the pump station and insufficient drainage capacity.

[0208] High water level support of the river system: Assume that the river water level gauge downstream of point A shows that the river water level is 3.5 meters at 14:00, and the upstream pipe bottom elevation of the first pipe section downstream of the lowest pipe point of the local rainwater pipe network at point A is 2.5 meters, and the cross-sectional size is 1.0 meter. The calculation condition is: 3.5≥2.5+1.0;

[0209] The conditions are met, indicating that the waterlogging point is affected by the high water level of the downstream river and drainage is poor.

[0210] 4. Analysis of insufficient design capacity of drainage network:

[0211] Calculate the rainstorm recurrence period: According to the rainstorm intensity formula compiled by the local meteorological department, the rainstorm recurrence period of rainfall is reversed. Assuming the maximum hourly rainfall Ih = 10mm / h, the maximum 3-hour rainfall I3h = 15mm, the rainstorm recurrence period P = 5 years is calculated. According to the "Outdoor Drainage Design Standard", the design recurrence period of the urban area where point A is located is 10 years. Therefore, P < Ps, and the above analysis is not valid, indicating that the design capacity of the local drainage network at the waterlogging point is insufficient.

[0212] 5. Analysis of high rainfall intensity:

[0213] Judging rainfall intensity: According to the calculated rainstorm recurrence period P = 5 years, and the design recurrence period of the urban area where point A is located is 10 years, it means that the maximum hourly rainfall reached 10 mm, and the maximum 3-hour rainfall reached 15 mm. The short-term rainfall intensity is relatively large, which is also one of the reasons for the waterlogging.

[0214] in conclusion:

[0215] Through intelligent analysis of the causes of waterlogging at point A, the system draws the following conclusions:

[0216] The main cause: there was misconnection and mixing of sewage upstream of the local rainwater pipe network. The average daily liquid level on dry days was 2.8 meters, which was relatively high and affected the flow capacity of rainwater on rainy days. At the same time, the pump station was abnormally opened and the drainage capacity was insufficient, resulting in the inability to discharge the accumulated water in time.

[0217] Secondary causes: The waterlogging points were affected by the high water level in the downstream river, resulting in poor drainage; in addition, the drainage network was not designed with sufficient capacity to cope with the high intensity of rainfall.

[0218] Suggested actions:

[0219] Repair the sewage mixing problem: immediately organize professionals to check the rainwater pipe network, repair the sewage mixing problems, and ensure the normal operation of the rainwater pipe network.

[0220] Optimize pump station operation: Check pump station equipment, repair faulty pumps, ensure that the pump station can operate normally on rainy days, and improve drainage capacity.

[0221] Improve drainage network design: Based on actual conditions, consider upgrading the drainage network and increasing its design recurrence period to cope with more intense rainfall.

[0222] Strengthen river management: coordinate with relevant departments to lower river water levels and reduce the impact on the drainage network.

[0223] Through the above analysis and suggestions, urban managers can take targeted measures to solve the waterlogging problem at point A, improve the efficiency of the city's drainage system, and reduce the occurrence of waterlogging.

[0224] The above embodiments are only used to illustrate the technical method of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical method of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical method of the present invention.

Claims

1. An intelligent analysis method for the causes of urban waterlogging, characterized in that: include: Step 1: Obtain waterlogging data in the target area; Step 2: Determine whether to issue an early warning of the water depth at the waterlogging point based on the waterlogging data; If yes, then issue a warning message and obtain rainfall data; if no, then continue monitoring and judgment; Step 3: Analyze the causes of waterlogging based on waterlogging data and rainfall data.

2. The intelligent analysis method for the causes of urban waterlogging according to claim 1 is characterized in that: The step of obtaining waterlogging data of a target area includes: The waterlogging data of the target area is collected in real time through data acquisition equipment; the target area refers to the waterlogging area to be monitored; the waterlogging data include: water depth at the waterlogging point, rainfall information, liquid level or flow of the rainwater pipe network, liquid level / flow of the main pipe, liquid level / flow of the outlet, river water level and operating status of the pump station.

3. The intelligent analysis method for the causes of urban waterlogging according to claim 1 is characterized in that: The determining whether to issue an early warning of the water depth at a waterlogging point based on waterlogging data includes: Extract the water depth of the waterlogging point in the real-time waterlogging data; Determine whether the water depth is greater than the preset water depth threshold; if yes, the water depth monitoring equipment installed at the water accumulation point will issue a warning message; if no, continue to monitor and judge.

4. The intelligent analysis method for the causes of urban waterlogging according to claim 1 is characterized in that: The obtaining of rainfall data comprises: Get the start time of rainfall; Get the end time of rainfall; Obtain rainfall period data; wherein the period data includes: maximum hourly rainfall during the rainfall period, maximum 3-hour rainfall, and cumulative rainfall during the rainfall period.

5. The intelligent analysis method for the causes of urban waterlogging according to claim 4 is characterized in that: The step of obtaining the start time of rainfall includes: S1: When the water depth monitoring equipment at the water accumulation point issues a warning message, the time when the warning message is generated is marked as the monitoring alarm time t0; the historical rainfall monitoring data before time t0 is extracted from the rainfall station closest to the water accumulation point; S2: record the nth hour before the monitoring alarm time t0 as t0-n, traverse the rainfall monitoring data from t0-n to t0 in chronological order, and find the first collection time of rainfall data greater than Vmin; where Vmin represents the minimum resolution of rainfall monitoring; S3: If no rainfall is found, the subsequent rainfall start time judgment is stopped, that is, if no significant rainfall occurs in the previous n hours, the water accumulation point alarm is a false alarm, and the current alarm is no longer tracked for rainfall events; S4: If the first rainfall data greater than Vmin is found, the data collection time is obtained and marked as the start time ts of the rainfall; S5: starting from time ts, traverse the rainfall monitoring data from time ts to the previous n hours again, and update the new rainfall start time by the same method as S2-S4; S6: Repeat step S5 until no rainfall data greater than Vmin is found, then stop judging and output the start time ts of this rainfall. If the output result is empty, it means that no rainfall occurred before the monitoring alarm was generated t0, then stop the dynamic tracking of the rainfall session.

6. The intelligent analysis method for the causes of urban waterlogging according to claim 4 is characterized in that: The step of obtaining the end time of rainfall includes: A1: Record the time after the monitoring alarm time t0 as t0+1, traverse the rainfall data from t0 to t0+1 in chronological order, and find the last rainfall data greater than Vmin; A2: If the last rainfall data greater than Vmin is found, the data collection time is obtained and marked as the end time te of the rainfall; A3: If it cannot be found, then record t0+1 as the end time te of the rainfall; A4: Traverse the rainfall monitoring data from time te to the next hour, find the last rainfall data greater than Vmin, obtain the data collection time, and update it to the new rainfall end time te; A5: Repeat A4 until no rainfall data greater than Vmin is found for n consecutive hours starting from the end time te of the rainfall. Then stop judging and output the end time te of this rainfall. If the output result is empty, it means that no rainfall has occurred after the monitoring alarm is generated at time t0, then stop the dynamic tracking of the rainfall session.

7. The intelligent analysis method for the causes of urban waterlogging according to claim 4 is characterized in that: The obtaining of rainfall period data includes: obtaining the maximum hourly rainfall during the rainfall period, the maximum 3-hour rainfall and the cumulative rainfall during the rainfall period; Obtaining the maximum hourly rainfall during the rainfall period: According to the start time ts and end time te of the rainfall period, the rainfall monitoring data in the time period is obtained; the cumulative rainfall in each 1-hour time interval is calculated by using a sliding time window, and the rainfall in all 1-hour time intervals is compared, and the maximum value is taken as the maximum hourly rainfall Ih; Maximum 3-hour rainfall: If the rainfall duration (te-ts) is greater than 3 hours, the monitoring data of the rainfall station in the rainfall period is obtained according to the rainfall start time ts and the rainfall end time te of the rainfall period. The rainfall at each 3-hour time interval is calculated using a sliding time window in the same way as the maximum hourly rainfall, and the maximum hourly rainfall I3h is obtained by comparison. If the rainfall duration (te-ts) is less than 2.5 hours, the maximum 3-hour rainfall I3h is not calculated; if the rainfall duration is 2.5 hours ≤ (te-ts) < 3 hours, the accumulated rainfall is directly used as the maximum 3-hour rainfall I3h; Obtaining the accumulated rainfall during the rainy period: Obtain the rainfall monitoring data within the rainfall period between the rainfall start time ts and the rainfall end time te, accumulate the rainfall Vi of all sampling points, and obtain the cumulative rainfall V; where i is the number of sampling points within the rainfall period.

8. The intelligent analysis method for the causes of urban waterlogging according to claim 1 is characterized in that: The analysis of the causes of waterlogging based on waterlogging data and rainfall data includes: The waterlogging is analyzed based on the preset causes of waterlogging; among them, the preset causes of waterlogging include: insufficient water collection capacity or siltation of rainwater inlets, sewage mixing in the rainwater pipe network or high water level operation in dry days, overflow caused by high water level in the sewage pipe network in dry days and inflow and infiltration in rainy days, siltation of the drainage pipe network downstream of the waterlogging point, abnormal opening of the pump station or insufficient drainage capacity, high water level support of the river system, insufficient design capacity of the drainage pipe network and high rainfall intensity.

9. The intelligent analysis method for the causes of urban waterlogging according to claim 8 is characterized in that: The analysis of waterlogging based on the preset causes of waterlogging includes: Analysis of insufficient water collection capacity or siltation of rainwater inlets: Extract the start time ts and end time te of the rainfall; after the rainfall ends, query the time series data of the water depth monitoring of the water accumulation point during the rainfall period to obtain the start time t0 of water accumulation; where the start time of water accumulation refers to the time when the water depth first rises to 0.15; In the time-series data of the low-point liquid level monitoring of the local rainwater pipe network, according to the starting waterlogging moment t0, interpolate within the rainfall period to obtain the liquid level monitoring value h0 corresponding to the starting waterlogging moment t0; in the time-liquid level monitoring data, find the moment tf before t0 and the corresponding monitored liquid level hf, find the moment tb after t0 and the corresponding monitored liquid level hb, and obtain h0 = (hb - hf) / (tb - tf)*(t0 - tf) + hf through linear interpolation; Judge whether the monitored liquid level h0 reaches the well depth d of the inspection well where the equipment is located or reaches the maximum monitored range, that is, hmin < h0 < d - α·FS, where hmin represents the minimum resolution of the liquid level monitoring equipment, α represents the full-scale error of the equipment, and FS represents the full scale of the equipment. If the condition is satisfied, it means that the surface waterlogging is not caused by the full-load operation of the pipe network and inspection wells, and the cause of waterlogging is: insufficient water collection capacity of the rainwater inlet or possible blockage; Analysis of sewage misconnection or high water level operation in dry weather in the rainwater pipe network: After the rainfall ends, query whether there is a diagnosis result of sewage misconnection disease at the low-point liquid level monitoring point of the local rainwater pipe network, and the characteristic time of the most recent disease diagnosis is within 30 days from the end time of the rainfall; if so, obtain the average dry-weather liquid level have of the most recent sewage misconnection disease diagnosis result; query the bottom elevation Hb of the inspection well where the low-point liquid level monitoring point of the local rainwater pipe network is located, and according to the pipe point-pipe section connection relationship of the rainwater pipe network, query the downstream pipe section of the inspection well where the liquid level monitoring point is located, and the upstream bottom elevation S_H and cross-sectional dimension D of the downstream pipe section; continue to judge whether the average dry-weather liquid level reaches the judgment condition for high water level operation have ≥ [0.4*D + (S_H - Hb)]. If the condition is satisfied, the cause of waterlogging at the waterlogging point is: there is sewage misconnection in the upstream of the local rainwater pipe network, and the average daily dry-weather liquid level is have, and the liquid level is relatively high, affecting the flow capacity of rainwater on rainy days; After the rainfall ends, if the diagnosis result of sewage misconnection disease cannot be queried 30 days before the rainfall end time te, then according to the dry-weather period judgment principle: the non-rainfall period after 72h of continuous non-rainfall, judge whether the rainfall start time ts is a dry-weather period. If it is a dry-weather period, in the time-series data of the low-point liquid level monitoring of the local rainwater pipe network, take the liquid level monitoring data hs corresponding to the rainfall start time ts. Specifically: in the time-liquid level monitoring data set, find the moments before and after ts and the corresponding monitored liquid levels, and obtain hs through linear interpolation accordingly. Then judge whether the liquid level hs reaches the judgment condition for high water level operation hs ≥ [0.4*D + (S_H - Hb)]. If the condition is satisfied, the cause of waterlogging at the waterlogging point is: the average dry-weather liquid level of the local rainwater pipe network is hsm, and the liquid level is relatively high, affecting the flow capacity of rainwater on rainy days; Analysis of sewage pipe network high water level in dry weather and inflow and infiltration during rainy days causing overflows: In the time-series data of the low-point liquid level monitoring of the local sewage pipe network, according to the starting waterlogging moment t0, interpolate within the rainfall period to obtain the liquid level monitoring value hws0 corresponding to the starting waterlogging moment t0; In the time-liquid level monitoring data, find the time tf and tb before and after t0 and the corresponding monitoring liquid levels hwsf and hwsb, and linearly interpolate to obtain hws0 = (hwsb-hwsf) / (tb-tf)*(t0-tf)+hwsf; Determine whether the monitoring liquid level hws0 reaches the depth deepws of the inspection well where the equipment is located or reaches the maximum monitoring range, that is, hws0 ≥ (deepws-α*FS), where α represents the full-scale error of the equipment and FS represents the full-scale range of the equipment; If the conditions are met, the local sewage pipe network low-point liquid level monitoring point will be further checked to see if there is any rainwater inflow and infiltration disease diagnosis result at the end of the previous natural month. If so, the cause of water accumulation is: there is a serious rainwater inflow and infiltration problem on rainy days, resulting in sewage overflow; According to the diagnosis results of rainwater inflow and infiltration diseases at the low-point liquid level monitoring point of the local sewage pipe network at the end of the previous natural month, the average monitoring liquid level hwsave of all dry days in one month is obtained; the bottom elevation Hwsb of the inspection well where the low-point liquid level monitoring point of the local sewage pipe network is located is queried, and according to the pipe point-pipe section connection relationship of the sewage pipe network, the downstream pipe section of the inspection well where the liquid level monitoring point is located, as well as the upstream pipe bottom elevation S_Hws and cross-sectional size Dws of the downstream pipe section are queried; and the judgment condition hwsave≥[Camax*Dws+(S_Hws-Hwsb)] of the dry day average liquid level is further judged to see whether it reaches the high water level operation, where Camax is the maximum design fullness of the sewage pipe specified in the "Outdoor Drainage Design Standard"; if the judgment condition is met, the reason for the waterlogging is further outputted as follows: the sewage is running at a high water level on dry days, the average liquid level is hwsave, and there is a serious rainwater inflow and infiltration problem on rainy days, resulting in sewage overflow; Analysis of clogging of drainage pipe network downstream of water accumulation point: After the rainfall is over, determine whether there are any blockage diagnosis results at the liquid level or flow monitoring points of the local rainwater pipe network and sewage pipe network, and whether the characteristic time of the most recent disease diagnosis is within 30 days from the end time of the rainfall te. If so, the cause of water accumulation at the water accumulation point is: the downstream pipe network may be blocked, affecting the flow capacity of rainwater on rainy days.

10. The intelligent analysis method for the causes of urban waterlogging according to claim 8 is characterized in that: The analysis of waterlogging based on the preset waterlogging causes also includes: Analysis of abnormal pump station start-up and insufficient drainage capacity: After the rainfall ends, query the water depth monitoring data of the waterlogging point during the rainfall period to obtain the time t0 when the waterlogging starts; based on the time t0 when the waterlogging starts, determine whether the on / off status of the pump station at the corresponding time can be queried within the subsequent Δt; where Δt is the collection period of the pump station operation status; If it can be found, the number of pumps M whose status is "off" and "faulty" at the corresponding time is counted. If M≥2, the cause of water accumulation is: abnormal start of the pump station and insufficient drainage capacity; Analysis of high water level support in river system: According to the water accumulation point and the local pipe network liquid level monitoring point, the corresponding outlet can be traced according to the topological relationship of the rainwater pipe network, and there is no rainwater pumping station in the middle. If there is a liquid level or flow monitoring device in the main pipe near the outlet, or there is a river water level meter near the outlet, the impact of the high water level downstream can be analyzed and determined; If there is no drainage outlet downstream, or there is a pumping station in the middle, or there is no corresponding river water level gauge and no corresponding main pipe liquid level or flow monitoring equipment, it is impossible to judge the high water level backwater of the river system, and there is no need to perform subsequent calculations and judgments; Taking the lowest pipe point of the local rainwater pipe network at the waterlogging point as the starting point, according to the connection relationship between pipe segments and pipe points, search for all pipe segments from the downstream of the lowest pipe point to the drainage outlet, and obtain the upstream pipe bottom elevation S_Hj, downstream pipe bottom elevation E_Hj and cross-sectional dimension Dj of each pipe segment in the pipe segment data table; where j represents the jth pipe segment; After the rainfall ends, query the water depth monitoring data at the waterlogging point during the rainfall period to obtain the starting waterlogging time t0; search for the water level gauge of the downstream river or lake water system at the waterlogging point, and obtain the river water level value L0 at the starting waterlogging time t0 in the river water level monitoring data by linear interpolation; where L0 is the absolute elevation of the river water level at the water surface; judge whether the first pipe segment downstream of the lowest pipe point of the local rainwater pipe network at the waterlogging point satisfies: L0≥(S_Hj+Dj). If it is satisfied, further count the number N of pipe segments that satisfy L0<S_Hj or L0<E_Hj among all pipe segments from the downstream of the lowest pipe point to the drainage outlet. If N = 0, the cause of waterlogging at the waterlogging point is: affected by the high water level backwater of the downstream river, the drainage is not smooth; If there is no river water level gauge near the drainage outlet downstream of the waterlogging point, but there is a corresponding liquid level gauge or flowmeter in the downstream main pipe, according to the starting waterlogging time t0, obtain the liquid level value h0 at time t0 in the liquid level monitoring data by linear interpolation method, and calculate the absolute water level corresponding to the liquid level (h0+H) according to the inner bottom elevation H of the pipe point; judge whether the first pipe segment downstream of the lowest pipe point of the local rainwater pipe network at the waterlogging point satisfies: (h0+H)≥(S_Hj+Dj). If it is satisfied, further count the number N of pipe segments that satisfy (h0+H)<S_Hj or (h0+H)<E_Hj among all pipe segments from the downstream of the lowest pipe point to the drainage outlet. If N = 0, the cause of waterlogging at the waterlogging point is: affected by the high water level backwater of the downstream, the drainage is not smooth; Analysis of insufficient design capacity of the drainage pipe network: Extract the start time ts, end time te of the rainfall, the maximum hourly rainfall Ih, the maximum 3-hour rainfall I3h and the cumulative rainfall Vi during the rainfall period; According to the rainstorm intensity formula compiled by the local meteorological department, inversely deduce the rainstorm recurrence period P of the rainfall: i = Ih / 60; q = 167f; ClgP = [(q(t+b)^n) / 167A1] - 1; Among them, the rainfall duration t is taken as 60 min; the parameters A1, C, b, n are obtained according to the local compiled design rainstorm intensity formula, f is the rainfall intensity, and the unit is mm / min; according to the maximum hourly rainfall Ih and the maximum 3-hour rainfall I3h of the rainfall event, calculate the corresponding rainstorm recurrence periods Ph and P3h respectively, and take the larger value of the two as the rainstorm recurrence period P of the rainfall = max(Ph, P3h); According to the urban area type where the waterlogging point is located, obtain the design return period Ps of the local drainage network according to the "Outdoor Drainage Design Standard". If P < Ps, the reason for waterlogging is: the design capacity of the local drainage network at the waterlogging point is insufficient; Analysis of large rainfall intensity: Based on the rainfall storm return period Pi and the design return period Ps of the local drainage network at the obtained waterlogging point, if Pi ≥ Ps, the reason for waterlogging is: the maximum hourly rainfall reaches Ihmm, the maximum 3-hour rainfall reaches I3hmm, and the short-term rainfall intensity is large.

Images