Urban flood disaster monitoring and early warning method

Abstract

The invention relates to the technical field of flood disaster monitoring, and discloses an urban flood disaster monitoring and early warning method, which comprises the steps of data acquisition, feature extraction, data analysis, comprehensive evaluation and early warning publication, and is characterized in that water regimen change can be mastered systematically through multi-dimensional data collection of urban water regimen from two key aspects of rainfall and water level; the rainfall intensity is finely divided, so that accurate cognition of the rainfall condition is facilitated; the flood risk is judged by counting related data of heavy rainfall, and the flood occurrence possibility is scientifically analyzed from the time dimension; the water level average height is calculated and compared with a warning threshold value, and the water level state can be rapidly determined; flood risk grades are accurately divided in combination with the water level height, the rising rate and the like, and targeted response is facilitated; a flood risk comprehensive index is calculated by comprehensively considering multiple factors such as rainfall and water level, flood early warning is scientifically and reasonably issued according to comparison between the index and a threshold value, and related parties are assisted to take flood prevention measures in time.

Description

Technical Field

[0001] The present invention relates to the technical field of flood disaster monitoring, and specifically relates to a method for monitoring and warning urban flood disasters. Background Art

[0002] Traditional methods for monitoring and warning urban flood disasters have many limitations. In terms of data collection, previous monitoring means were relatively single, and may only focus on collecting data on either precipitation or water level, unable to comprehensively and systematically reflect the overall situation of urban water conditions. For example, relying solely on a few rain gauges to obtain precipitation data makes it difficult to accurately grasp the precipitation differences in different areas of the city; the water level monitoring at key positions of water bodies is not comprehensive enough, and some important drainage pipes, small lakes and other locations may be missed, resulting in the inability to accurately grasp the overall water level dynamics of the city.

[0003] At the data analysis level, traditional methods lack in-depth analysis of key elements such as precipitation intensity, duration, and water level changes. Making early warning judgments simply based on single precipitation data or water level data has poor accuracy and cannot effectively predict the occurrence of flood disasters in advance. For example, judging whether a flood may occur only based on the total precipitation, while ignoring the combined effects of precipitation intensity and duration, or when analyzing the water level, not considering factors such as the water level rising rate, making the early warning results often unreliable and unable to provide strong support for urban flood control and disaster reduction work.

[0004] In addition, the traditional early warning release method is not scientific and refined enough, lacking accurate grading of flood risk levels, and it is difficult to meet the needs of urban refined management and residents' early prevention. Therefore, it is urgent to develop a comprehensive, accurate and scientific method for monitoring and warning urban flood disasters. Summary of the Invention

[0005] The purpose of the present invention is to provide a method for monitoring and warning urban flood disasters, which solves the technical problems proposed in the background art.

[0006] The purpose of the present invention can be achieved by the following technical solutions:

[0007] A method for monitoring and warning urban flood disasters includes the following steps:

[0008] The first step, data collection:

[0009] By pre-establishing multiple rain gauges distributed in different areas of the city, collect precipitation data, and at the same time pre-set water level monitoring points at multiple key positions of water bodies in the city to measure water level height data;

[0010] The second step, feature extraction:

[0011] Feature extraction is performed on precipitation data and water level data, and the regional average precipitation of each region in the city and the water level change rate at key positions of each water body are obtained;

[0012] Step 3. Data analysis:

[0013] Precipitation analysis and water level analysis are carried out based on the results of feature extraction;

[0014] Step 4. Comprehensive evaluation:

[0015] Comprehensive evaluation is carried out based on the results of precipitation analysis and water level analysis, and the comprehensive flood risk index is determined through comprehensive evaluation;

[0016] Step 5. Early warning release:

[0017] It is determined whether to issue a flood warning based on the comprehensive flood risk index.

[0018] As a further solution of the present invention: the feature extraction method is as follows:

[0019] Step 2.1. Mark the precipitation data as P i，t , where i represents the number of rainfall monitoring stations in different regions, t represents the acquisition time node, i = 1, 2,..., n, t = 1, 2,..., e, n represents the number of rainfall monitoring stations, that is, the number of different regions, and e is the number of acquisition time nodes;

[0020] By:

[0021] Calculate the regional average precipitation PJ of each region in the city t ;

[0022] Step 2.2. Record the water level data as W j，t , where j represents the number of different water level monitoring points, j = 1, 2,..., m, and m represents the number of water level monitoring points.

[0023] By:

[0024] Calculate the water level change rate WB at the key positions of each water body j，t ;

[0025] In the formula, t0 is the time interval between two adjacent acquisition time nodes.

[0026] As a further solution of the present invention: among them, the key positions of the water body include main rivers, lakes, and drainage pipes.

[0027] As a further solution of the present invention: the precipitation analysis method is as follows:

[0028] Step 3.1.1: First, calculate the precipitation intensity PQ at each collection time node through:

[0029] Calculate the precipitation intensity PQ at each collection time node t ;

[0030] Step 3.1.2: Then, extract the preset precipitation intensity threshold PQy, and then compare the precipitation intensity PQt at each collection time node with the precipitation intensity threshold PQy:

[0031] When PQ t > 1.5×PQy, mark it as a heavy precipitation event, and record the corresponding collection time node as the heavy precipitation time node;

[0032] When PQ t < 0.5×PQy, mark it as a light precipitation event, and record the corresponding collection time node as the light precipitation time node;

[0033] When 0.5×PQy ≤ PQ t ≤ 1.5×PQy, mark it as a moderate precipitation event, and record the corresponding collection time node as the moderate precipitation time node;

[0034] Step 3.1.3: Then, conduct statistics on the duration of heavy precipitation events, and count the duration of heavy precipitation events and the number of heavy precipitation events;

[0035] The method for counting the duration of heavy precipitation is as follows: within the observation period, following the time trend, start timing when PQ t > 1.5×PQy, and stop timing until PQ t ≤ 1.5×PQy. Then, compare the time counted between them with the preset duration threshold. When the time counted between them is greater than the preset duration threshold, record it as the duration of heavy precipitation and mark it as QT k , k = 1, 2,..., c, where c represents the number of durations of heavy precipitation recorded within the observation period, that is, the number of heavy precipitation events;

[0036] Step 3.1.4: Next, calculate the proportion RQ of the total heavy precipitation time in the time of this observation period through:

[0037] Calculate the proportion RQ of the total heavy precipitation time in the time of this observation period;

[0038] In the formula, T1 is the duration of the observation period, is the total heavy precipitation time;

[0039] Step 3.1.5: Compare the proportion RQ of the total heavy precipitation time in the time of this observation period with the preset proportion threshold RQy of heavy precipitation time:

[0040] When RQ ≥ RQy, it is determined that there is a flood risk in the city;

[0041] When RQ < RQy, it is determined that there is no flood risk in the city.

[0042] As a further solution of the present invention: the water level analysis method is as follows:

[0043] Step 3.2.1, through:

[0044] Calculate the average water level height PW at the water level monitoring points in the city j ;

[0045] Then extract the pre-set water level warning threshold Wy, and then compare the average water level height PW at the water level monitoring points j with the water level warning threshold Wy:

[0046] When PW j ≥ Wy, it is determined that the water level at this water level monitoring point is too high;

[0047] When PW j < Wy, it is determined that the water level at this water level monitoring point is moderate;

[0048] Step 3.2.2, then through:

[0049] Calculate the water level rising rate WS of each water level monitoring point during the observation period j ;

[0050] Step 3.2.3, then extract the pre-set rising rate threshold WSy, and then compare the water level rising rate WS of each water level monitoring point at each acquisition time node j with the rising rate threshold WSy:

[0051] When WS j > 1.3 × WSy and PW j ≥ Wy, it is determined that the flood risk of the corresponding water level monitoring point is at a high risk level;

[0052] When 1.3 × WSy ≥ WS j ≥ 0.7 × WSy and PW j ≥ Wy, it is determined that the flood risk of the corresponding water level monitoring point is at a medium risk level.

[0053] As a further solution of the present invention: the premise of comprehensive evaluation is that at least one of RQ ≥ RQy, PW j ≥ Wy and WS j ≥ WSy holds.

[0054] As a further solution of the present invention, the comprehensive evaluation method is as follows:

[0055] By:

[0056] Calculate the comprehensive flood risk index E;

[0057] Where β 1 and β 2 are preset weight coefficients, H j is a step function. When PW j ≥Wy, then H j = 1, otherwise H j = 0.

[0058] As a further solution of the present invention, the determination method of whether to issue a flood warning is as follows:

[0059] Compare the comprehensive flood risk index E with the preset comprehensive flood risk index threshold Ey:

[0060] When E > Ey, issue a flood warning;

[0061] When E ≤ Ey, do not issue a flood warning.

[0062] As a further solution of the present invention, when E > 2×Ey, issue a red flood warning; when 2×Ey ≥ E > 1.6×Ey, issue an orange flood warning; when 1.6×Ey ≥ E > 1.3×Ey, issue a yellow flood warning; when 1.3×Ey ≥ E > Ey, issue a blue flood warning.

[0063] Advantages of the present invention:

[0064] In the present invention, by setting rain gauges in different areas of the city to collect precipitation data, and setting water level monitoring points in main rivers, lakes, drainage pipes, etc. to measure water level height data, multi-dimensional data collection of urban water conditions from two key aspects of precipitation and water level is realized, laying a foundation for subsequent comprehensive and accurate analysis of urban flood disaster risks, and enabling a more systematic grasp of the overall water condition changes in the city.

[0065] In the present invention, the precipitation intensity at the collection time node is carefully divided into heavy precipitation, moderate precipitation, and light precipitation events, and clearly defined according to the corresponding thresholds, which helps to accurately grasp the occurrence of different precipitation levels and makes the understanding of precipitation conditions clearer and more accurate.

[0066] In the present invention, by statistically analyzing the duration of heavy precipitation and the number of its events, calculating the proportion of the total time of heavy precipitation in the observation period, and comparing it with a preset threshold to determine whether there is a flood risk in the city, the possibility of flood occurrence is deeply analyzed from the time dimension of precipitation, enabling more scientific early judgment of flood risk.

[0067] In the present invention, by calculating the average water level height at the water level monitoring point and comparing it with the water level warning threshold, it can quickly determine whether the water level is too high, intuitively understand the water level status of each monitoring point, and provide a basic basis for subsequent risk assessment.

[0068] In the present invention, by calculating the water level rising rate, combining it with the water level height and comparing it with a preset rising rate threshold, the flood risk of the corresponding water level monitoring point is accurately classified into high-risk levels, medium-risk levels, etc., realizing an effective assessment of flood risk levels and facilitating targeted countermeasures.

[0069] In the present invention, by comprehensively considering various factors such as precipitation-related flood risk, water level height, and water level rising rate, a comprehensive flood risk index is calculated, and based on the comparison of this index with a preset comprehensive flood risk index threshold, corresponding flood warnings are issued according to different intervals, realizing the scientific and reasonable issuance of flood warnings, enabling relevant parties such as urban managers and residents to take corresponding flood control measures in a timely manner according to the accurate warning levels, ensuring urban safety, and reducing losses that may be brought by flood disasters. BRIEF DESCRIPTION OF THE DRAWINGS

[0070] The present invention will be further described below with reference to the accompanying drawings.

[0071] Figure 1 It is a schematic flow chart of a method for monitoring and warning urban flood disasters according to the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0072] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. All other embodiments obtained by those of ordinary skill in the art without creative efforts based on the embodiments of the present invention belong to the scope of protection of the present invention.

[0073] Embodiment 1

[0074] Please refer to Figure 1 As shown, the present invention is a method for monitoring and warning urban flood disasters, including the following steps:

[0075] First step, data collection:

[0076] By pre - establishing multiple rainfall monitoring stations distributed in different areas of the city, precipitation data is collected and marked as P i，t , where i represents the number of the rainfall monitoring station in different areas, t represents the collection time node, i = 1, 2, …… n, t = 1, 2, …… e, n represents the number of rainfall monitoring stations, that is, the number of different areas, and e is the number of collection time nodes;

[0077] These areas cover the commercial areas, residential areas, industrial areas, park green spaces, and low - lying areas prone to waterlogging in the city, etc.; through reasonable distribution, it is ensured that precipitation data in every corner of the city can be comprehensively and accurately collected;

[0078] At the same time, water level monitoring points are pre - set at multiple key positions of water bodies in the city to measure water level height data and mark it as W j，t , where j represents the number of different water level monitoring points, j = 1, 2, …… m, and m represents the number of water level monitoring points;

[0079] In this embodiment, the key positions of water bodies include main rivers, lakes, drainage pipes, etc.; for main rivers, monitoring points are set at key positions such as different river sections, bends, and intersections; for lakes, monitoring is carried out at positions such as the lake inlet, the center of the lake, and the lake outlet; for drainage pipes, monitoring points are set at positions such as pipe diameter changes, drainage outlets, and easily blocked sections;

[0080] Step 2. Feature extraction:

[0081] Step 2.1. By:

[0082] Calculate the regional average precipitation PJ of each area in the city t ;

[0083] Step 2.2. By:

[0084] Calculate the water level change rate WB of each key position of the water body j，t ;

[0085] In the formula, t0 is the time interval between two adjacent collection time nodes;

[0086] Step 3. Data analysis:

[0087] Step 3.1. Precipitation analysis:

[0088] Step 3.1.1. First, by:

[0089] Calculate the precipitation intensity PQ of each collection time node t ;

[0090] Step 3.1.2: Subsequently, extract the pre-set precipitation intensity threshold PQy, and then compare the precipitation intensity PQt at each acquisition time node with the precipitation intensity threshold PQy:

[0091] When PQ t > 1.5 × PQy, it is marked as a heavy precipitation event, and the corresponding acquisition time node is recorded as a heavy precipitation time node;

[0092] When PQ t < 0.5 × PQy, it is marked as a light precipitation event, and the corresponding acquisition time node is recorded as a light precipitation time node;

[0093] When 0.5 × PQy ≤ PQ t ≤ 1.5 × PQy, it is marked as a moderate precipitation event, and the corresponding acquisition time node is recorded as a moderate precipitation time node;

[0094] Step 3.1.3: Then, conduct statistics on the duration of heavy precipitation events, and count the duration of heavy precipitation events and the number of heavy precipitation events;

[0095] The method for statistics of the duration of heavy precipitation is as follows: within the observation period, following the time trend, start timing when PQ t > 1.5 × PQy, and stop timing until PQ t ≤ 1.5 × PQy. Then, compare the time counted between them with the pre-set duration threshold. When the time counted between them is greater than the pre-set duration threshold, it is recorded as the duration of heavy precipitation and marked as QT k , k = 1, 2,... c, where c represents the number of times recorded as the duration of heavy precipitation within the observation period, that is, the number of heavy precipitation events;

[0096] Step 3.1.4: Then, through:

[0097] Calculate the proportion RQ of the total heavy precipitation time in the time of this observation period;

[0098] In the formula, T1 is the duration of the observation period, is the total heavy precipitation time;

[0099] Step 3.1.5: Compare the proportion RQ of the total heavy precipitation time in the time of this observation period with the pre-set proportion threshold RQy of heavy precipitation time:

[0100] When RQ ≥ RQy, it is determined that there is a flood risk in the city;

[0101] When RQ < RQy, it is determined that there is no flood risk in the city;

[0102] Step 3.2, Water level analysis:

[0103] Step 3.2.1, By:

[0104] Calculate the average water level height PW at the water level monitoring points in the city j ;

[0105] Then extract the preset water level warning threshold Wy, and then compare the average water level height PW at the water level monitoring point j with the water level warning threshold Wy:

[0106] When PW j ≥Wy, it is determined that the water level at the water level monitoring point is too high;

[0107] When PW j <Wy, it is determined that the water level at the water level monitoring point is moderate;

[0108] Step 3.2.2, Then by:

[0109] Calculate the water level rising rate WS of each water level monitoring point during the observation period j ;

[0110] Step 3.2.3, Then extract the preset rising rate threshold WSy, and then compare the water level rising rate WS at each collection time node of each water level monitoring point j with the rising rate threshold WSy:

[0111] When WS j >1.3×WSy and PW j ≥Wy, it is determined that the flood risk of the corresponding water level monitoring point is at a high risk level;

[0112] When 1.3×WSy≥WS j ≥0.7×WSy and PW j ≥Wy, it is determined that the flood risk of the corresponding water level monitoring point is at a medium risk level.

[0113] In this embodiment, rainfall monitoring stations are widely established in different areas of the city. At the same time, water level monitoring points are set at key positions of water bodies such as major rivers, lakes, and drainage pipes, which can comprehensively collect precipitation and water level height data, providing rich and accurate basic information for subsequent analysis; by calculating the regional average precipitation and water level change rate through specific formulas, the key features reflecting urban precipitation and water level changes can be effectively extracted, providing a strong basis for flood risk analysis; not only calculating the precipitation intensity, but also grading the precipitation intensity, counting the duration of heavy precipitation and the proportion of heavy precipitation time, and comparing with the corresponding thresholds, the possibility of flood caused by precipitation is evaluated from multiple angles, improving the accuracy of the evaluation; by calculating the average water level height and water level rising rate, and comparing with their respective thresholds, and combining the two to judge the flood risk level of the water level monitoring point, the flood risk related to the water level is scientifically and reasonably evaluated.

[0114] Embodiment 2

[0115] Please refer to Figure 1 As shown in the figure, as Embodiment 2 of the present invention, when the present application is specifically implemented, compared with Embodiment 1, the technical solution of this embodiment is only different from that of Embodiment 1 in that on the basis of Embodiment 1, this embodiment further includes the steps of comprehensive evaluation and early warning release;

[0116] The comprehensive evaluation step is that when at least one of RQ≥RQy, PW j ≥Wy and WS j ≥WSy holds, comprehensive evaluation is carried out accordingly;

[0117] This trigger condition fully considers the influence of multiple key factors such as precipitation and water level on flood risk. As long as one of the factors reaches the early warning standard, the comprehensive evaluation process is started to ensure that any possible flood risk will not be missed;

[0118] The comprehensive evaluation method is as follows:

[0119] By:

[0120] Calculate the comprehensive flood risk index E;

[0121] where β 1 and β 2 are preset weight coefficients, H j is a step function. When PW j ≥Wy, then H j =1, otherwise H j =0;

[0122] The early warning release is to compare the comprehensive flood risk index E with the preset comprehensive flood risk index threshold Ey, and then determine whether to issue a flood warning according to the comparison result:

[0123] When E > Ey, a flood warning is issued;

[0124] Among them, the flood warning information is released to relevant departments and the public through various channels such as text messages, radio, television, social media, and the urban emergency warning system. At the same time, the warning information includes detailed information such as the approximate scope of the flood risk and the possible degree of impact, so that relevant departments and the public can take timely countermeasures;

[0125] When E ≤ Ey, no flood warning is issued;

[0126] The threshold of the comprehensive flood risk index is preset in advance by analyzing a large amount of historical flood data and combining the flood control ability and the acceptable risk range of the city;

[0127] Based on Embodiment 1, in this embodiment, when the relevant indicators of precipitation and water level meet certain conditions, a comprehensive evaluation is carried out. By calculating the comprehensive flood risk index and considering multiple factors, compared with the single-factor determination in Embodiment 1, the urban flood risk can be evaluated more comprehensively and accurately; comparing the comprehensive flood risk index with the preset threshold to determine whether to issue a warning makes the warning decision more scientific and reasonable, improving the accuracy and reliability of the warning.

[0128] Embodiment 3

[0129] Please refer to Figure 1 As shown, as Embodiment 3 of the present invention, in the specific implementation of this application, compared with Embodiment 1 and Embodiment 2, the technical solution of this embodiment is to combine and implement the solutions of the above Embodiment 1 and Embodiment 2. The difference between the technical solution of this embodiment and Embodiment 1 and Embodiment 2 is only that when determining to issue a flood warning, the level of the flood warning is also determined;

[0130] Specifically:

[0131] When E > 2 × Ey, a red flood warning is issued. At this time, the city faces extremely serious flood risks, and relevant departments should immediately initiate the highest-level emergency response, organize the evacuation of personnel and the transfer of materials, and strengthen the flood control and emergency rescue work in key areas;

[0132] When 2 × Ey ≥ E > 1.6 × Ey, an orange flood warning is issued. The city is in a state of high flood risk. Relevant departments should strengthen duty shifts, organize rescue teams to standby, and be ready to carry out rescue work at any time. At the same time, the public is reminded to minimize going out and take good self-protection;

[0133] When 1.6 × Ey ≥ E > 1.3 × Ey, a yellow flood warning is issued. There are relatively large flood risks in the city. Relevant departments should strengthen the monitoring of water levels and precipitation, clean drainage pipes in a timely manner, and do a good job in the reserve of flood control materials;

[0134] When 1.3×Ey ≥ E > Ey, a blue flood warning is issued for cities with certain flood risks. Relevant departments should closely monitor weather changes and water levels, and remind the public to pay attention to preventing problems such as possible waterlogging.

[0135] Based on Embodiment 2, this embodiment further determines the flood warning level according to the comparison between the comprehensive flood risk index and different thresholds, providing a more detailed warning for different levels of flood risks, which helps relevant departments and the public take more targeted response measures.

[0136] Embodiment 4

[0137] Please refer to Figure 1 As shown, as Embodiment 4 of the present invention, when this application is specifically implemented, compared with Embodiment 1, Embodiment 2, and Embodiment 3, the technical solution of this embodiment is to combine the solutions of the above Embodiment 1, Embodiment 2, and Embodiment 3 for implementation.

[0138] This embodiment combines the solutions of Embodiment 1, 2, and 3 for implementation, fully integrating the advantages of each embodiment, forming a complete, comprehensive, and detailed urban flood disaster monitoring and warning system, maximizing the monitoring and warning capabilities for urban flood disasters, and providing strong support for the prevention and response to urban flood disasters.

[0139] The above formulas are all dimensionless and take their numerical values for calculation. The formulas are obtained by collecting a large amount of data and performing software simulation to obtain a formula that is closest to the actual situation. The preset parameters and threshold selection in the formulas are set by those skilled in the art according to the actual situation.

[0140] The above is only the specific implementation manner of this application, but the protection scope of this application is not limited thereto. Any person skilled in the art can easily think of changes or substitutions within the technical scope disclosed in this application, and all should be covered by the protection scope of this application. Therefore, the protection scope of this application should be subject to the protection scope of the claimed rights.

Claims

1. A method for monitoring and early warning of urban flood disasters, characterized in that: The following steps are involved: Step 1: Data collection: By setting up multiple rainfall monitoring stations distributed in different areas of the city in advance to collect precipitation data, and setting up water level monitoring points at multiple key locations of water bodies in the city in advance to measure water level height data; Step 2: Feature extraction: Perform feature extraction from precipitation data and water level height data, and obtain the regional average precipitation in each area of ​​the city and the water level change rate at each key location of each water body; Step 3: Data Analysis: Conduct precipitation analysis and water level analysis based on feature extraction processing results; Step 4: Comprehensive evaluation: Conduct a comprehensive assessment based on the results of precipitation analysis and water level analysis, and determine the comprehensive flood risk index through the comprehensive assessment; Step 5: Warning release: Whether a flood warning should be issued is determined based on the comprehensive flood risk index.

2. The urban flood disaster monitoring and early warning method according to claim 1 is characterized in that: The feature extraction process is as follows: Step 2.1: Mark the precipitation data as P i，t , where i represents the number of rainfall monitoring stations in different regions, t represents the collection time node, i = 1, 2, ... n, t = 1, 2, ... e, n represents the number of rainfall monitoring stations, that is, the number of different regions, and e is the number of collection time nodes; pass: Calculate the regional average precipitation PJ for each area in the city t ; Step 2.2: Record the water level data as W j，t , where j represents the number of different water level monitoring points, j = 1, 2, ... m, and m represents the number of water level monitoring points; pass: Calculate the water level change rate WB at each key location of the water body j，t ; Where t0 is the time interval between two adjacent acquisition time nodes.

3. The urban flood disaster monitoring and early warning method according to claim 2 is characterized in that: The precipitation analysis method is as follows: Step 3.1.1, first pass: Calculate the precipitation intensity PQ at each collection time node t ; Step 3.1.2: Then extract the pre-set precipitation intensity threshold PQy, and then compare the precipitation intensity PQt at each acquisition time node with the precipitation intensity threshold PQy: When PQ t >1.5×PQy, it is marked as a heavy precipitation event, and the corresponding collection time node is recorded as a heavy precipitation time node; When PQ t <0.5×PQy, it is marked as a weak precipitation event, and the corresponding acquisition time node is recorded as a weak precipitation time node; When 0.5×PQy≤PQ t ≤1.5×PQy, it is marked as a moderate precipitation event, and the corresponding collection time node is recorded as a moderate precipitation time node; Step 3.1.3, then count the duration of heavy rainfall events, and count the duration of heavy rainfall events and the number of heavy rainfall events; Step 3.1.4, then pass: Calculate the proportion of the total time of heavy precipitation in this observation period RQ; Where T1 is the duration of the observation period, QT k is the duration of heavy rainfall events, k = 1, 2, ... c, c represents the number of heavy rainfall durations recorded in the observation period, that is, the number of heavy rainfall events, is the total duration of heavy precipitation; Step 3.1.5: Compare the total time proportion of heavy precipitation in this observation period RQ with the preset threshold value of heavy precipitation time proportion RQy: When RQ ≥ RQy, the city is judged to be at risk of flooding; When RQ<RQy, it is determined that there is no flood risk in the city.

4. The urban flood disaster monitoring and early warning method according to claim 3 is characterized in that: In step 3.1.3, the duration of heavy rainfall is calculated as follows: within the observation period, according to the time trend, in PQ t >1.5×PQy, start timing until PQ t The timing is stopped when ≤1.5×PQy, and the statistical time is compared with the preset duration threshold. When the statistical time is greater than the preset duration threshold, it is recorded as the duration of heavy rainfall.

5. The urban flood disaster monitoring and early warning method according to claim 3 is characterized in that: The water level analysis method is as follows: Step 3.2.1, by: Calculate the average water level PW at the water level monitoring points in the city j ; Then the preset water level warning threshold Wy is extracted, and the average water level height PW at the water level monitoring point is calculated. j Compare with the water level warning threshold Wy: When PW j When ≥Wy, the water level at the water level monitoring point is judged to be too high; When PW j When <Wy, the water level at the water level monitoring point is judged to be moderate; Step 3.2.2, then pass: Calculate the water level rise rate WS at each water level monitoring point during the observation period j ; Step 3.2.3, then extract the preset rising rate threshold WSY, and then convert the water level rising rate WS at each acquisition time node at each water level monitoring point into j Compare with the rise rate threshold WSY: When WS j >1.3×WSy and PW j When ≥Wy, the flood risk of the corresponding water level monitoring point is judged to be at a high risk level; When 1.3×WSy≥WS j ≥0.7×WSy and PW j When ≥Wy, the flood risk of the corresponding water level monitoring point is judged to be at a medium risk level.

6. The urban flood disaster monitoring and early warning method according to claim 5 is characterized in that: The premise of comprehensive evaluation is: RQ ≥ RQy, PW j ≥Wy and WS j ≥When at least one of the conditions in WSY is true.

7. The urban flood disaster monitoring and early warning method according to claim 6 is characterized in that: The comprehensive evaluation method is as follows: pass: Calculate the comprehensive flood risk index E; Among them, β1 and β2 are the preset weight coefficients, H j is a step function, when PW j ≥Wy, then H j =1, otherwise H j =0.

8. The urban flood disaster monitoring and early warning method according to claim 7 is characterized in that: Whether a flood warning is issued is determined as follows: Compare the flood risk comprehensive index E with the preset flood risk comprehensive index threshold Ey: When E>Ey, a flood warning is issued; When E≤Ey, no flood warning will be issued.

9. The urban flood disaster monitoring and early warning method according to claim 8 is characterized in that: When E>2×Ey, a red flood warning is issued; when 2×Ey≥E>1.6×Ey, an orange flood warning is issued; when 1.6×Ey≥E>1.3×Ey, a yellow flood warning is issued; when 1.3×Ey≥E>Ey, a blue flood warning is issued.

10. The urban flood disaster monitoring and early warning method according to claim 1, characterized in that: in, Key water locations include major rivers, lakes, and drainage pipes.

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