Urban inland inundation simulation multi-scale slicing method

Abstract

The invention relates to the technical field of urban inland inundation, in particular to an urban inland inundation simulation multi-scale slicing method, which comprises the following steps of: based on urban remote sensing and geographic information data, collecting urban terrain and land utilization data, cleaning the data, uniformly processing formats of differentiated data sources, and obtaining a cleaned data set. According to the method, city remote sensing and geographic information data are utilized, cities are classified according to topographic features and land utilization, and regional slicing is performed in combination with a geographic information system, so that the hydrological model can reflect specific conditions of each region more accurately, and hydrological parameters can be adjusted according to specific conditions of different regions; the prediction model can better adapt to future environmental changes, simulate the water flow dynamic state under a differentiated rainfall scene and predict the ponding depth of each region, can effectively identify a potential waterlogging risk region, and provides powerful decision support for urban planning and infrastructure optimization.

Description

Technical Field

[0001] The present invention relates to the technical field of urban waterlogging, and in particular to a multi-scale slicing method for simulating urban waterlogging. Background Art

[0002] The field of urban waterlogging technology involves the interdisciplinary application of hydrology, water resources management, urban planning, and disaster prevention. Its primary goal is to study and address waterlogging issues in urban areas during extreme rainfall events, often caused by factors such as poor surface drainage, insufficient sewer capacity, and overdevelopment. Techniques employed in this field include rainfall simulation, drainage system modeling, terrain and geomorphological analysis, and the design of emergency response plans. By deeply understanding the mechanisms of urban waterlogging, effective prediction and management tools are being developed to mitigate the impact of waterlogging on the urban environment and residents' lives.

[0003] The multi-scale slicing method for urban flooding simulation is a technical tool for urban flooding risk analysis and management. By meticulously slicing the urban drainage system and terrain at different scales, a multi-level model is created. This method simulates water flow dynamics and water accumulation at various scales under varying rainfall conditions, thereby identifying potential risk areas and weak links. Its primary applications include providing a scientific basis for urban planning and renovation, helping decision-makers develop more effective drainage facility layouts and emergency response plans, and improving cities' ability to respond to sudden rainfall events and mitigate potential loss of property and life.

[0004] Traditional approaches to urban flooding caused by extreme rainfall events lack sufficient data integration capabilities and sophisticated analysis of topographic and land use data. Drainage system modeling in these approaches fails to fully account for the diversity and complexity of topography, resulting in an inability to accurately predict and manage flooding risks in practical applications. Furthermore, traditional approaches are limited in their ability to adjust hydrological parameters to accommodate future engineering changes. Consequently, in practice, the design and planning of urban drainage systems cannot quickly adapt to environmental changes or new urban development needs, increasing the risk of urban disasters under extreme climate conditions. This lack of flexibility in adjusting hydrological model parameters limits the speed and efficiency of urban responses to sudden flooding events. Summary of the Invention

[0005] The purpose of the present invention is to solve the shortcomings of the prior art and propose a multi-scale slicing method for urban waterlogging simulation.

[0006] To achieve the above objectives, the present invention adopts the following technical solution: a multi-scale slicing method for simulating urban waterlogging, comprising the following steps:

[0007] S1: Based on the city's remote sensing and geographic information data, collect urban terrain and land use data, perform data cleaning, unify the formats of different data sources, and obtain the cleaned data set;

[0008] S2: Based on the cleaned dataset, combined with the geographic information system, the dataset is regionally sliced, and cities are classified according to terrain characteristics and land use differences to obtain multi-scale urban terrain layered data;

[0009] S3: Based on the multi-scale urban terrain layered data, analyzing the water flow velocity, drainage system capacity, and land water absorption rate of the differentiated areas, calculating the drainage capacity index of the differentiated areas, and obtaining hydrological parameter analysis results;

[0010] S4: Based on the hydrological parameter analysis results, adjust the preset values ​​of water flow velocity and drainage system capacity to match future engineering changes, and obtain adjusted hydrological simulation parameters;

[0011] S5: Based on the adjusted hydrological simulation parameters, simulate the water flow dynamics under differentiated rainfall scenarios, predict the water depth in each area, identify potential waterlogging risk areas, and obtain waterlogging risk prediction information;

[0012] S6: Based on the waterlogging risk prediction information, analyze the existing urban planning and infrastructure layout, identify the deficiencies in the current drainage system, formulate urban planning and infrastructure optimization measures, and obtain urban planning adjustment recommendation information.

[0013] As a further solution of the present invention, the cleaned data set includes standardized terrain height data, land use classification data and completed remote sensing image data; the multi-scale urban terrain stratification data includes the basic hydrological sensitivity rating of the region, regional boundary definition and land use type; the hydrological parameter analysis results include the water flow velocity, drainage capacity index and land water absorption data of each region; the adjusted hydrological simulation parameters include adjusted water flow velocity parameters and drainage capacity parameters; the urban waterlogging risk prediction information includes the urban waterlogging risk level of each region, the predicted waterlogging depth and the location of urban waterlogging; the urban planning adjustment recommendation information includes drainage system improvement measures, land use adjustment recommendations and the location of flood control measures.

[0014] As a further solution of the present invention, based on the remote sensing and geographic information data of the city, urban terrain and land use data are collected, data cleaning is performed, and the formats of the differentiated data sources are unified to obtain the cleaned data set. The specific steps are as follows:

[0015] S101: Based on the city's remote sensing and geographic information data, collect urban terrain data, extract elevation values, slope changes, and surface features from the data item by item, and filter the data to remove erroneous elevation and slope information to obtain preliminary screened urban terrain data;

[0016] S102: Based on the initially screened urban terrain data, outlier removal is performed, data exceeding a reasonable range in the elevation and slope data is reviewed, abnormal data is excluded, and missing data is supplemented by interpolation estimation to optimize the continuity of the terrain data and obtain completed data;

[0017] S103: Based on the completed data, uniformly process the data from different sources, including adjusting the coordinate system, resolution, and data format, optimizing the consistency and availability of the data, and obtaining a cleaned data set.

[0018] As a further solution of the present invention, based on the cleaned dataset, combined with a geographic information system, the dataset is regionally sliced, and cities are classified according to terrain characteristics and land use differences to obtain multi-scale urban terrain layered data. Specifically, the steps are as follows:

[0019] S201: Based on the cleaned data set, using a geographic information system, segmenting the urban area according to a preset spatial grid, identifying the boundaries and features of differentiated areas, dividing the city into multiple geographic units, and obtaining urban area slice data;

[0020] S202: Based on the urban area slice data, classify the terrain of each geographical unit, identify and divide the terrain height, slope change, and river distribution in the differentiated units, and correspond the terrain feature data with the geographical units to obtain terrain feature classification data;

[0021] S203: Based on the terrain feature classification data, combined with the regional waterlogging records and land use records, the waterlogging risks of differentiated regions are assessed according to the regional terrain and land use, to obtain multi-scale urban terrain stratification data.

[0022] As a further solution of the present invention, based on the multi-scale urban terrain layered data, the water flow velocity, drainage system capacity, and land water absorption rate of differentiated areas are analyzed, and the drainage capacity index of the differentiated areas is calculated to obtain the hydrological parameter analysis results. Specifically, the steps are as follows:

[0023] S301: Based on the multi-scale urban terrain layered data, each region is analyzed to extract regional terrain information and land use characteristics, identify water flow paths and drainage system locations, and classify drainage characteristics to obtain differentiated regional drainage basic data;

[0024] S302: Based on the differentiated regional drainage basic data, the water flow velocity of each region is calculated. In combination with the terrain height, slope, and capacity of the current drainage system, the water flow rate of each region and the drainage velocity of the drainage system are measured. The land water absorption capacity of the differentiated plots is also calculated to obtain differentiated regional hydrological parameters.

[0025] S303: Based on the differentiated regional hydrological parameters, the water flow velocity, drainage capacity and soil water absorption rate parameters of each region are integrated, and a weighted multi-factor integrated analysis method is used to calculate the drainage capacity index of each region to obtain the hydrological parameter analysis results.

[0026] As a further embodiment of the present invention, the weighted multi-factor integrated analysis method is according to the formula:

[0027]

[0028] Calculate the differential regional drainage capacity index, where V represents water flow velocity, C represents drainage system capacity, S represents land water absorption rate, and w V 、w C and w S are the weight coefficients of water flow velocity, drainage system capacity and land water absorption rate, respectively, and DI is the drainage capacity index.

[0029] As a further solution of the present invention, based on the hydrological parameter analysis results, the preset values ​​of the water flow velocity and the capacity of the drainage system are adjusted to match future engineering changes, and the steps of obtaining adjusted hydrological simulation parameters are specifically as follows:

[0030] S401: Based on the hydrological parameter analysis results, extract drainage project data of differentiated areas, obtain construction progress, construction speed and construction target data of the drainage project, and obtain drainage project related data;

[0031] S402: Calculating the construction progress of the target period based on the drainage project related data, analyzing the impact of the drainage project on the water flow velocity and drainage system capacity during the target period, and obtaining project impact data;

[0032] S403: Based on the engineering impact data, the drainage capacity of each area is re-evaluated, and the water flow velocity and drainage system capacity parameters of the target period are adjusted to match the drainage engineering impact of the target period, thereby obtaining adjusted hydrological simulation parameters.

[0033] As a further embodiment of the present invention, based on the adjusted hydrological simulation parameters, the water flow dynamics under differentiated rainfall scenarios are simulated to predict the water depth in each area, identify potential waterlogging risk areas, and obtain waterlogging risk prediction information in the following steps:

[0034] S501: Based on the adjusted hydrological simulation parameters, a rainfall scenario of the target area is input, the rainfall amount and rainfall duration of the area are set as differentiated scenarios, and a water flow simulation is performed to obtain water flow dynamic data under the differentiated rainfall scenarios;

[0035] S502: Based on the water flow dynamic data under the differentiated rainfall scenarios, combined with the terrain height and the efficiency of the drainage system, the water depth of each area under the target rainfall scenario is calculated to obtain regional water depth data;

[0036] S503: Based on the regional waterlogging depth data, a regional risk assessment model is used to analyze the waterlogging risk areas. By comparing the difference between the waterlogging depth and the regional drainage capacity, the risk areas with severe waterlogging are identified to obtain waterlogging risk prediction information.

[0037] As a further solution of the present invention, the regional risk assessment model is according to the formula:

[0038]

[0039] Calculate the waterlogging risk index RI A , where D A Represents the actual water depth, C A represents the regional drainage capacity, λ is the stability constant, K is the adjustment coefficient of the risk index, RI A It is the waterlogging risk index.

[0040] As a further embodiment of the present invention, based on the waterlogging risk prediction information, the existing urban planning and infrastructure layout are analyzed to identify deficiencies in the current drainage system, formulate urban planning and infrastructure optimization measures, and obtain urban planning adjustment recommendation information in the following steps:

[0041] S601: Based on the waterlogging risk prediction information, analyze the current urban planning layout, compare the risk area with the current urban drainage system layout, identify the deficiencies and potential weaknesses of the drainage system, and obtain drainage system deficiency analysis results;

[0042] S602: Based on the drainage system deficiency analysis results, the current urban infrastructure layout is evaluated. By combining risk areas and drainage system information, key areas for infrastructure optimization and renovation directions are identified to obtain infrastructure optimization information.

[0043] S603: Based on the infrastructure optimization information and in combination with the city's planning and development goals, the overall urban planning layout is adjusted, and urban planning optimization measures are formulated, including drainage system expansion and development restrictions in sensitive areas, to obtain urban planning adjustment recommendation information.

[0044] Compared with the prior art, the advantages and positive effects of the present invention are:

[0045] In the present invention, by utilizing urban remote sensing and geographic information data, urban terrain and land use data are collected and integrated, thereby enhancing the accuracy and application scope of the data set, classifying cities according to terrain characteristics and land use, and combining with the geographic information system for regional slicing, so that the hydrological model can more accurately reflect the specific conditions of each region, thereby improving the practical application value and prediction accuracy of the model. By analyzing multi-scale urban terrain layered data, the hydrological parameters can be adjusted according to the specific conditions of different regions, so that the prediction model can better adapt to future environmental changes, simulate the water flow dynamics under differentiated rainfall scenarios and predict the water depth of each region, which can effectively identify potential waterlogging risk areas, provide strong decision-making support for urban planning and infrastructure optimization, enhance the ability to respond to sudden rainfall events, and also help to reduce possible property and life losses. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] Figure 1 It is a schematic diagram of the main steps of the present invention;

[0047] Figure 2 This is a schematic diagram of the refinement of S1 of the present invention;

[0048] Figure 3 This is a schematic diagram of the refinement of S2 of the present invention;

[0049] Figure 4 This is a schematic diagram of the refinement of S3 of the present invention;

[0050] Figure 5 This is a schematic diagram of the refinement of S4 of the present invention;

[0051] Figure 6 This is a schematic diagram of the refinement of S5 of the present invention;

[0052] Figure 7 This is a detailed schematic diagram of S6 of the present invention. DETAILED DESCRIPTION

[0053] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0054] In the description of the present invention, it should be understood that the terms "length," "width," "up," "down," "front," "back," "left," "right," "vertical," "horizontal," "top," "bottom," "inside," "outside," and the like, indicating positions or relationships, are based on the positions or relationships shown in the accompanying drawings and are intended only to facilitate the description of the present invention and simplify the description. They do not indicate or imply that the devices or elements referred to must have a specific orientation, be constructed, or operate in a specific orientation. Therefore, they should not be construed as limiting the present invention. Furthermore, in the description of the present invention, "plurality" means two or more, unless otherwise expressly and specifically defined.

[0055] See also Figure 1 The present invention provides a technical solution: a multi-scale slicing method for simulating urban waterlogging, comprising the following steps:

[0056] S1: Based on the city's remote sensing and geographic information data, collect urban terrain and land use data, integrate remote sensing images, perform data cleaning, remove outliers, fill in missing values, and unify the formats of different data sources to obtain a cleaned dataset;

[0057] S2: Based on the cleaned dataset, combined with the geographic information system, the dataset is sliced ​​into regions, and cities are classified according to terrain characteristics and land use differences to obtain multi-scale urban terrain layered data;

[0058] S3: Based on multi-scale urban terrain layered data, analyze the water flow velocity, drainage system capacity, and land water absorption rate of differentiated areas, calculate the drainage capacity indicators of differentiated areas, and integrate the data to obtain hydrological parameter analysis results;

[0059] S4: Based on the hydrological parameter analysis results and combined with the drainage project data, the hydrological parameters are adjusted to adjust the preset values ​​of the water flow velocity and the capacity of the drainage system to match the future project changes, and the adjusted hydrological simulation parameters are obtained;

[0060] S5: Based on the adjusted hydrological simulation parameters, simulate the water flow dynamics under differentiated rainfall scenarios, predict the water depth in each area, analyze the simulation results, identify potential waterlogging risk areas, and obtain waterlogging risk prediction information;

[0061] S6: Based on the waterlogging risk prediction information, analyze the existing urban planning and infrastructure layout, identify the deficiencies in the current drainage system, formulate urban planning and infrastructure optimization measures, and obtain urban planning adjustment recommendations.

[0062] The cleaned dataset includes standardized terrain height data, land use classification data, and complete remote sensing image data. The multi-scale urban terrain stratification data includes the basic hydrological sensitivity rating of the region, regional boundary definition, and land use type. The hydrological parameter analysis results include the water flow velocity, drainage capacity index, and land water absorption data of each region. The adjusted hydrological simulation parameters include the adjusted water flow velocity parameters and drainage capacity parameters. The waterlogging risk prediction information includes the waterlogging risk level of each region, the predicted waterlogging depth, and the location of waterlogging. The urban planning adjustment recommendation information includes drainage system improvement measures, land use adjustment recommendations, and the location of flood control measures.

[0063] See also Figure 2 Based on the city's remote sensing and geographic information data, we collect urban terrain and land use data, integrate remote sensing images, clean the data, remove outliers, fill in missing values, and unify the formats of differentiated data sources. The specific steps to obtain the cleaned data set are as follows:

[0064] S101: Based on the city's remote sensing and geographic information data, collect urban terrain data, extract elevation values, slope changes, and surface features from the data item by item, and filter the data to remove erroneous elevation and slope information to obtain preliminary screened urban terrain data;

[0065] Based on the city's remote sensing and geographic information data, urban terrain data collection is conducted. Elevation information is extracted from multi-source remote sensing data. Using a digital elevation model as a basis, the elevation value, slope change, and surface features of each data point are analyzed. Each data point is extracted item by item, and the slope is calculated using terrain analysis tools. A surface feature classification algorithm is used to distinguish between various landforms. By setting elevation error thresholds and slope change thresholds, data points that fall outside the error range are eliminated. For example, data points with elevation errors exceeding ±3 meters or slope changes exceeding 45 degrees are identified as erroneous information and eliminated. This results in a preliminarily screened urban terrain dataset that eliminates obvious elevation errors and unreasonable slope changes.

[0066] S102: Based on the initial screening of urban terrain data, outliers are removed, and data outside the reasonable range in the elevation and slope data are reviewed and excluded. Missing data are filled in through interpolation estimation, and the continuity of the terrain data is optimized to obtain the completed data;

[0067] Based on the initial screening of urban terrain data, outliers are removed. Reasonable data ranges are set. For example, elevation data should be between the known highest and lowest points in the city, and slopes should not exceed the maximum slope of the natural terrain. Data points in the elevation and slope data that fall outside these reasonable ranges are reviewed, and outliers are identified and removed using box plots. For missing elevation or slope information, spatial interpolation methods such as Kriging interpolation are used to estimate the missing data, optimize data continuity and integrity, and obtain the completed data.

[0068] S103: Based on the completed data, the data from different sources are uniformly processed, including adjusting the coordinate system, resolution, and data format, optimizing the consistency and availability of the data, and obtaining a cleaned data set.

[0069] Based on the completed data, uniformly process data from different sources, adjust the coordinate systems of each data source to a unified geographic coordinate system, ensure the spatial consistency of all data, unify the data resolution, upsample low-resolution data, and downsample high-resolution data to match the standard resolution required by the project, convert data in different formats into a unified format, such as from Shapefile to GeoJSON, to ensure data availability and compatibility, and obtain a cleaned dataset.

[0070] See also Figure 3 Based on the cleaned dataset, combined with the geographic information system, the dataset is sliced ​​into regions, and cities are classified according to terrain characteristics and land use differences. The specific steps to obtain multi-scale urban terrain layered data are as follows:

[0071] S201: Based on the cleaned data set, using a geographic information system, the urban area is segmented according to a preset spatial grid, the boundaries and features of differentiated areas are identified, and the city is divided into multiple geographic units to obtain urban area slice data;

[0072] Based on the cleaned dataset, a geographic information system (GIS) was used to set a grid resolution, such as 50 meters by 50 meters, to demarcate urban areas. By comparing terrain elevation and land cover types within different grids, spatial analysis tools, such as edge detection algorithms, were used to identify significant differences between regions. The boundaries and features of these differentiated areas were then marked, and based on these boundaries, the city was divided into distinct geographic units, each representing a different type of terrain or surface feature. This process ensured that the terrain characteristics within each geographic unit were relatively consistent while being distinct from adjacent units, resulting in urban area slice data.

[0073] S202: Based on the urban area slice data, the terrain of each geographical unit is classified, and the terrain height, slope change, and river distribution in the differentiated units are identified and divided. The terrain feature data is matched with the geographical units to obtain terrain feature classification data;

[0074] Based on urban area slice data, a detailed terrain classification was performed for each geographic unit. Using terrain analysis tools, statistical analysis was performed on the elevation and slope data for each unit, identifying the primary terrain trends within each unit and analyzing the distribution of rivers within the unit, including their length, direction, and relative position to the terrain. Terrain features were associated with each geographic unit using a geographic information system (GIS), constructing a comprehensive terrain feature classification dataset encompassing terrain categories (such as plains, hills, and mountains) and river distribution. This dataset details the physical geographic characteristics of each geographic unit, providing the necessary foundation for terrain-related risk analysis.

[0075] S203: Based on the terrain feature classification data, combined with the regional waterlogging records and land use records, the waterlogging risk of differentiated areas is assessed according to the regional topography and land use, and multi-scale urban terrain stratification data is obtained.

[0076] Based on terrain classification data and combining regional flooding records with land use records, the team assessed flooding risk in each region. The team analyzed land use types within the region, such as residential areas, industrial areas, and farmland. Each land use type has distinct hydrological characteristics, affecting surface water discharge and infiltration. Combined with terrain data, particularly slope and river distribution, a hydrological model was used to calculate the potential depth and flow direction of waterlogging in each region under extreme rainfall events. This analysis quantitatively assessed the regional flooding risk level, resulting in a stratified urban terrain risk dataset encompassing multiple scales and layers, which identified potential risk areas.

[0077] See also Figure 4 Based on multi-scale urban terrain layered data, the water flow velocity, drainage system capacity and land water absorption rate of differentiated areas are analyzed, the drainage capacity indicators of differentiated areas are calculated, and the data are integrated to obtain the hydrological parameter analysis results. The specific steps are as follows:

[0078] S301: Based on multi-scale urban terrain layered data, analyze each region, extract regional terrain information and land use characteristics, identify water flow paths and drainage system locations, and classify drainage characteristics to obtain differentiated regional drainage basic data;

[0079] Based on multi-scale urban terrain layering data, the terrain and land use characteristics of each area are carefully extracted. A digital elevation model (DEM) is used to determine the elevation and slope information of the area, and combined with land cover data to identify various types of land use, such as residential areas, commercial areas or public facilities areas. The water flow path is analyzed through a geographic information system to identify the location of natural and artificial drainage systems, such as rivers, ditches and sewer systems. For different types of drainage facilities, drainage characteristics are classified, considering their design capacity and actual operating efficiency, and integrated to form differentiated regional drainage basic data, marking the drainage characteristics of each area, including water flow path, drainage facility type and status.

[0080] S302: Based on the differentiated regional drainage basic data, the water flow velocity of each region is calculated. In combination with the terrain height, slope, and the capacity of the current drainage system, the water flow rate of each region and the drainage velocity of the drainage system are measured. The land water absorption capacity of the differentiated plots is also calculated to obtain the differentiated regional hydrological parameters.

[0081] When calculating the water flow velocity in each area based on differentiated regional drainage basic data, the water flow Q is calculated according to the formula: Q = A·V, taking into account the terrain height and slope.

[0082] Where Q represents water flow, A represents cross-sectional area, and V represents water velocity.

[0083] Detailed explanation of the formula and the process of formula calculation and derivation:

[0084] To calculate the specific water flow rate, it is necessary to determine the cross-sectional area A and water velocity V of each area. The cross-sectional area can be obtained from topographic maps and on-site measurements, while the water velocity is directly measured using a flow meter. Assuming the cross-sectional area of ​​a certain area is 10 square meters and the water velocity is measured to be 2 meters per second, the water flow rate Q is calculated as follows:

[0085] Q=10m 2 ×2m / s=20m 3 / s

[0086] The results show that 20 cubic meters of water flow through the area per second. This data provides a direct reference for assessing the adequacy of the area's drainage system and whether drainage capacity expansion is necessary. If the drainage system's design capacity is lower than this value, drainage facilities need to be optimized or upgraded to prevent potential flooding risks.

[0087] When calculating the land water absorption capacity of each area, the land type and terrain slope are combined to calculate the land water absorption rate S according to the formula: S = P·(1-I).

[0088] In the formula, S represents the soil water absorption rate, P represents rainfall, and I represents the surface impermeability.

[0089] Detailed explanation of the formula and the process of formula calculation and derivation:

[0090] Land absorption capacity reflects how much water the land can absorb under specific rainfall conditions. The impermeability, I, is determined by the land cover type. For example, densely built-up areas have higher impermeability, while grassland or farmland have lower impermeability. Assuming a rainfall of 30 mm / hour in a given area, the land type is urban green space, and the impermeability, I, is estimated to be 0.2. The calculation process for the land absorption, S, is as follows:

[0091] S=30mm / h·(1-0.2)=24mm / h

[0092] The results show that, taking into account surface cover, the area can absorb 24 mm of rain per hour. This data is important for assessing the potential risk of flooding and drainage needs in the area.

[0093] S303: Based on the differentiated regional hydrological parameters, the water flow velocity, drainage capacity and land water absorption rate parameters of each region are integrated, and a weighted multi-factor integrated analysis method is used to calculate the drainage capacity index of each region to obtain the hydrological parameter analysis results.

[0094] Weighted multi-factor integrated analysis method, according to the formula:

[0095]

[0096] Calculate the differentiated regional drainage capacity index, where V represents the water flow velocity, reflecting the rate of regional water flow; C represents the drainage system capacity, quantifying the treatment capacity of drainage facilities in the region; S represents the land water absorption rate, describing the efficiency of land absorption of rainfall; w V 、w C and w S are the weight coefficients of water flow velocity, drainage system capacity and land water absorption rate, respectively. The weights are obtained through analysis of environmental characteristics and historical flood data to ensure that the formula reflects the needs and priorities of actual conditions. DI is the drainage capacity index.

[0097] formula:

[0098]

[0099] Parameter details and how to obtain them:

[0100] Water flow velocity V: A parameter that characterizes the speed of water flow, usually measured directly in water bodies such as rivers and drainage channels using a flow meter.

[0101] Drainage system capacity C: It indicates the maximum volume of water flow that the drainage system can handle per unit time. It is often obtained from technical data provided by the urban planning department or water bureau, or calculated through drainage system design parameters.

[0102] Soil water absorption rate (S): This reflects how much precipitation the land absorbs per unit time. This is usually related to the land type (such as soil type, vegetation cover, and building coverage). Its value can be obtained through on-site measurement or estimated based on historical data.

[0103] Weight coefficient w V 、w C and w S The coefficients are derived from historical data analysis and expert assessment, reflecting the relative importance of various parameters in assessing a system's drainage capacity. These weights are specific to the site and are typically set by urban planning departments or water conservancy engineering expert groups based on specific geographic and climatic conditions.

[0104] Calculation example:

[0105] Set the following parameter values:

[0106] V = 3 m / s (representing a medium flow velocity).

[0107] C = 2000 cubic meters per second (representing the drainage system capacity of a large city).

[0108] S = 5 mm / h (representing urban green spaces with a certain water absorption capacity).

[0109] Weight coefficient w V =0.3, w C =0.5, w S =0.2 (coefficient assumption based on expert evaluation).

[0110] Calculation process:

[0111]

[0112] The calculated DI value indicates that a given area has a high enough drainage efficiency under the given conditions to handle common rainfall events. This indicator helps urban planners and engineers understand the drainage capacity of a specific area and plan or adjust infrastructure accordingly.

[0113] See also Figure 5 Based on the hydrological parameter analysis results and combined with the drainage project data, the hydrological parameters are adjusted to adjust the preset values ​​of water flow velocity and drainage system capacity to match future project changes. The specific steps to obtain the adjusted hydrological simulation parameters are as follows:

[0114] S401: Based on the hydrological parameter analysis results, extract drainage project data of differentiated areas, obtain construction progress, construction speed and construction target data of the drainage project, and obtain drainage project related data;

[0115] Based on the hydrological parameter analysis results, drainage project data for each area was extracted. This included detailed construction progress information, such as the length of pipe network installed, the number of pump stations installed, and the number of completed drainage ditches. Construction speed data recorded the construction team's work rate on a monthly basis from project inception to the present, including the daily area worked and the main construction equipment used. Construction target data was set based on the project plan and urban drainage needs, clearly defining the target values ​​for improving drainage capacity. Through data collection and integration, a drainage project-related dataset was formed, encompassing construction progress, speed, and goals.

[0116] S402: Calculate the construction progress of the target period based on the drainage project related data, analyze the impact of the drainage project on the water flow velocity and drainage system capacity during the target period, and obtain project impact data;

[0117] Based on the current drainage project construction progress P0, the construction speed v s , and time increment Δt, to calculate the construction progress of the future target period, the formula can be used: P t =P0+v s ·Δt.

[0118] Where, P t represents the construction progress of the target period, P0 is the current construction progress, v s It represents the increase in construction speed per unit time, and Δt is the time increment.

[0119] Detailed explanation of the formula and the process of formula calculation and derivation:

[0120] Assume that the current construction progress P0 is 30%, the estimated time period Δt is 10 days, and the construction speed v s If the construction progress during the target period is 0.5% per day, the construction progress during the target period is calculated as:

[0121] P t =30%+0.5%×10=35%

[0122] It indicates that construction progress will increase from 30% to 35% in the next 10 days.

[0123] To analyze the impact of drainage projects on drainage system capacity during the target period, the formula: C t =C0+

[0124] ΔC. The calculation of ΔC depends on the construction progress P tRelative to the change in P0, for example, every 1% increase in construction progress can increase the drainage capacity by 10 cubic meters.

[0125] Where C t represents the drainage system capacity during the target period, C0 is the current capacity, ΔC is the capacity increase brought about by the construction, and is calculated by the formula ΔC=10×(P t -P0) is calculated.

[0126] Detailed explanation of the formula and the process of formula calculation and derivation:

[0127] Assuming the current drainage system capacity C0 is 1000 cubic meters, and the calculated construction progress increases by 5% (from 30% to 35%), the capacity increase is calculated as:

[0128] ΔC = 10 × (35% - 30%) = 10 × 5% = 50 cubic meters

[0129] Therefore, upon completion of construction, the total capacity of the drainage system will increase to:

[0130] C t =1000+50=1050 cubic meters

[0131] It states that the construction project will increase the total capacity of the drainage system to 1,050 cubic meters.

[0132] S403: Based on the project impact data, the drainage capacity of each area is re-evaluated, and the water flow velocity and drainage system capacity parameters of the target period are adjusted to match the drainage project impact of the target period, and the adjusted hydrological simulation parameters are obtained.

[0133] Based on the project impact data, the drainage capacity of each area was reassessed, and the flow velocity parameters and drainage system capacity parameters were adjusted accordingly. Hydrological simulation software was used to simulate adjusted flow and drainage conditions, taking into account the possibility of partial functional failure or capacity reduction of the drainage system during construction. Taking into account the specific topography and land use conditions of the region, the drainage capacity of each area during the construction period was reassessed, and areas with problems were analyzed in detail. Through evaluation and adjustment, adjusted hydrological simulation parameters were formed. These parameters can more accurately reflect the drainage conditions and response measures of each area under the influence of drainage project construction, thereby ensuring the efficiency and safety of the urban drainage system.

[0134] See also Figure 6 Based on the adjusted hydrological simulation parameters, the water flow dynamics under differentiated rainfall scenarios are simulated, the water depth in each area is predicted, the simulation results are analyzed, and potential waterlogging risk areas are identified. The specific steps for obtaining waterlogging risk prediction information are as follows:

[0135] S501: Based on the adjusted hydrological simulation parameters, the rainfall scenario of the target area is input, the rainfall amount and rainfall duration of the area are set as differentiated scenarios, and water flow simulation is performed to obtain water flow dynamic data under the differentiated rainfall scenarios;

[0136] Based on the adjusted hydrological simulation parameters, rainfall scenarios are set for the target areas. Based on historical meteorological data and forecast models, differentiated rainfall scenarios are set, such as the amount and duration of rainfall in different regions, tailored to their geographical and climatic characteristics. Using hydrological simulation software, rainfall parameters are input and the model is run to simulate the impact of rainfall events on the urban drainage system. This simulation yields flow dynamics data for each region under the set rainfall scenarios, such as flow velocity, direction, and potential waterlogging areas. This data helps us understand the response of the urban drainage system and potential changes in flow dynamics under specific rainfall conditions.

[0137] S502: Based on the water flow dynamic data under differentiated rainfall scenarios, combined with the terrain height and the efficiency of the drainage system, the water depth of each area under the target rainfall scenario is calculated to obtain regional water depth data;

[0138] Based on the water flow dynamics data under differentiated rainfall scenarios, combined with the terrain height and the efficiency of the drainage system, the water depth of each area under the target rainfall scenario is calculated using the formula: Calculate the water depth for each area under the target rainfall scenario.

[0139] Where R A represents rainfall intensity, T A represents the duration of rainfall, Q A Represents the drainage capacity of the drainage system, A S The surface representing the region.

[0140] Detailed explanation of the formula and the process of formula calculation and derivation:

[0141] Rainfall intensity R A and rainfall duration T A It can be obtained from meteorological data and is usually determined based on forecasts or historical data. A It is the actual data obtained from the drainage system design and maintenance records. The surface area of ​​the area A S Usually obtained through geographic information systems or field measurements.

[0142] Calculation example:

[0143] Set the following parameter values: R A =20 mm / h (higher rainfall intensity), T A = 3 hours (rainfall event duration), Q A=50 cubic meters / second (drainage system performance), A S = 10,000 square meters (area surface area).

[0144] Calculation process:

[0145]

[0146] Calculation result D A =0.001m, indicating that minor flooding is expected in this area. While the drainage system performs well, it may still face challenges under extreme rainfall conditions. The results can help urban planners and emergency management agencies assess the efficiency of existing drainage facilities and consider whether improvements or expansions are needed to better cope with future high-intensity rainfall events.

[0147] S503: Based on regional waterlogging depth data, a regional risk assessment model is used to analyze waterlogging risk areas. By comparing the difference between waterlogging depth and regional drainage capacity, the risk areas with severe waterlogging are identified to obtain waterlogging risk prediction information.

[0148] Regional risk assessment model, according to the formula:

[0149]

[0150] Calculate the waterlogging risk index RI A , where D A Represents the actual water depth, C A represents the regional drainage capacity, that is, the maximum drainage volume designed for the region, λ is a stability constant to ensure that the denominator is non-zero, K is the adjustment coefficient of the risk index to increase the sensitivity of the calculation results, RI A It is the waterlogging risk index.

[0151] formula:

[0152]

[0153] Parameter details and how to obtain them:

[0154] D A Actual water depth, measured in meters, is typically obtained through field measurements or estimates from rainfall models. This is data obtained through direct observation or calculation, reflecting the amount of water accumulated in an area following a specific rainfall event.

[0155] C A : Regional drainage capacity is the data obtained based on the drainage system design documents or calculated through the hydraulic model, which indicates the maximum water treatment capacity of the drainage system under design conditions.

[0156] λ: A small positive number added to ensure calculation stability, usually set to 0.1 to avoid the denominator being zero.

[0157] K: The adjustment coefficient of the risk index, set to 100, is used to adjust the risk index to a reasonable measure to better evaluate and compare the risk levels of different regions.

[0158] Calculation example:

[0159] The specific design parameters are as follows:

[0160] D A = 0.5 m, which represents the depth of water accumulation observed in a certain area after a heavy rainfall event.

[0161] C A =0.3m, indicating the maximum drainage depth designed for the drainage system in this area.

[0162] According to the formula Perform the calculation:

[0163] Calculate the difference and its square root plus a positive adjustment:

[0164] |D A -C A |=|0.5-0.3|=0.2

[0165]

[0166] Calculate the risk index:

[0167]

[0168] Calculation results RI A =124.7, indicating that the risk of urban flooding in this area is very high, considering that the water depth is much higher than the design capacity of the drainage system. The value provides a quantitative risk assessment for urban planning and emergency management, indicating that the area needs to improve drainage facilities or take other flood control measures to mitigate potential flood damage.

[0169] See also Figure 7 Based on the waterlogging risk prediction information, the existing urban planning and infrastructure layout are analyzed to identify the deficiencies in the current drainage system, and urban planning and infrastructure optimization measures are formulated to obtain urban planning adjustment recommendations. The specific steps are as follows:

[0170] S601: Based on the waterlogging risk prediction information, analyze the current urban planning layout, compare the risk area with the current urban drainage system layout, identify the deficiencies and potential weaknesses of the drainage system, and obtain drainage system deficiency analysis results;

[0171] Based on flood risk prediction information, the current urban planning layout is analyzed. Using a geographic information system, a map of flood risk areas is overlaid on the existing urban drainage system layout to identify areas where drainage facilities are most closely associated with risk areas. The design capacity, age, and most recent maintenance status of regional drainage systems are analyzed to identify deficiencies and potential weaknesses in the drainage system, such as insufficient drainage pipe diameters, outdated drainage grids, or improper maintenance. This information is integrated to generate a drainage system deficiency analysis.

[0172] S602: Based on the drainage system deficiency analysis results, evaluate the current urban infrastructure layout, combine risk areas and drainage system information, identify key areas for infrastructure optimization and transformation directions, and obtain infrastructure optimization information;

[0173] Based on the drainage system deficiency analysis results, the current urban infrastructure layout is evaluated. Areas with insufficient drainage capacity and high risk are highlighted, and the existing infrastructure's service to these areas is assessed. Considering the impact of drainage deficiencies on urban functions and residents' lives, key areas for infrastructure optimization and improvement directions are identified. For example, improvement measures such as increasing the density of drainage pipe networks, upgrading outdated pipe networks, or adding temporary water storage areas are proposed to generate information for infrastructure optimization.

[0174] S603: Based on the infrastructure optimization information and combined with the city's planning and development goals, adjust the overall urban planning layout and formulate urban planning optimization measures, including drainage system expansion and development restrictions in sensitive areas, to obtain urban planning adjustment recommendation information.

[0175] Based on infrastructure optimization information and combined with the city's planning and development goals, the overall urban planning layout is adjusted. Taking into account the city's future development needs, such as population growth forecasts, economic development directions, and environmental protection requirements, specific urban planning optimization suggestions are formulated, including expanding the drainage system in high-risk waterlogging areas, adding green infrastructure such as rain gardens and permeable pavement to increase ground moisture infiltration, and restricting the development of sensitive areas, such as prohibiting the construction of large commercial centers or residential areas in waterlogged areas. Urban planning adjustment suggestion information is obtained.

[0176] The above are merely preferred embodiments of the present invention and do not limit the present invention in any other form. Any technician familiar with the profession may use the technical content disclosed above to change or modify it into an equivalent embodiment with equivalent changes and apply it to other fields. However, any simple modification, equivalent change and modification made to the above embodiment based on the technical essence of the present invention without departing from the content of the technical solution of the present invention shall still fall within the scope of protection of the technical solution of the present invention.

Claims

1. A multi-scale slicing method for urban waterlogging simulation, characterized in that: The following steps are involved: Based on the city's remote sensing and geographic information data, collect urban terrain and land use data, perform data cleaning, and unify the formats of differentiated data sources to obtain cleaned data sets; Based on the cleaned data set, combined with the geographic information system, the data set is regionally sliced, and the cities are classified according to the terrain characteristics and land use differences to obtain multi-scale urban terrain layered data; Based on the multi-scale urban terrain stratification data, the water flow velocity, drainage system capacity and land water absorption rate of the differentiated areas are analyzed, the drainage capacity index of the differentiated areas is calculated, and the hydrological parameter analysis results are obtained; Based on the hydrological parameter analysis results, the preset values ​​of water flow velocity and drainage system capacity are adjusted to match future engineering changes, thereby obtaining adjusted hydrological simulation parameters; Based on the adjusted hydrological simulation parameters, the water flow dynamics under differentiated rainfall scenarios are simulated, the water depth of each area is predicted, potential waterlogging risk areas are identified, and waterlogging risk prediction information is obtained; Based on the waterlogging risk prediction information, the existing urban planning and infrastructure layout are analyzed to identify the deficiencies in the current drainage system, formulate urban planning and infrastructure optimization measures, and obtain urban planning adjustment recommendation information.

2. The multi-scale slicing method for urban waterlogging simulation according to claim 1, characterized in that: The cleaned data set includes standardized terrain height data, land use classification data and completed remote sensing image data, the multi-scale urban terrain stratification data includes the basic hydrological sensitivity rating of the region, regional boundary definition and land use type, the hydrological parameter analysis results include the water flow velocity, drainage capacity index and land water absorption data of each region, the adjusted hydrological simulation parameters include adjusted water flow velocity parameters and drainage capacity parameters, the waterlogging risk prediction information includes the waterlogging risk level of each region, the predicted waterlogging depth and the location of waterlogging, and the urban planning adjustment suggestion information includes drainage system improvement measures, land use adjustment suggestions and flood control measures location.

3. The multi-scale slicing method for urban waterlogging simulation according to claim 1, characterized in that: Based on the remote sensing and geographic information data of the city, the urban terrain and land use data are collected, the data is cleaned, and the formats of the differentiated data sources are processed uniformly. The specific steps to obtain the cleaned data set are as follows: Based on the remote sensing and geographic information data of the city, urban terrain data is collected, and the elevation values, slope changes and surface features in the data are extracted item by item. The data is screened to remove erroneous elevation and slope information to obtain preliminary screened urban terrain data; Based on the preliminary screening of urban terrain data, outliers are removed, data beyond a reasonable range in elevation and slope data are reviewed, abnormal data are excluded, and missing data are supplemented by interpolation estimation, the continuity of terrain data is optimized, and completed data is obtained; Based on the completed data, the data from different sources are uniformly processed, including adjusting the coordinate system, resolution and data format, optimizing the consistency and availability of the data, and obtaining a cleaned data set.

4. The multi-scale slicing method for urban waterlogging simulation according to claim 1, characterized in that: Based on the cleaned data set, combined with the geographic information system, the data set is sliced ​​into regions, and cities are classified according to terrain characteristics and land use differences to obtain multi-scale urban terrain layered data. The specific steps are: Based on the cleaned data set, using a geographic information system, the urban area is segmented according to a preset spatial grid, the boundaries and features of the differentiated areas are identified, the city is divided into multiple geographic units, and urban area slice data is obtained; Based on the urban area slice data, the terrain of each geographical unit is classified, the terrain height, slope change, and river distribution in the differentiated unit are identified and divided, and the terrain feature data is matched with the geographical unit to obtain terrain feature classification data; Based on the terrain feature classification data, combined with the regional waterlogging records and land use records, the waterlogging risks of differentiated areas are assessed according to the regional topography and land use, and multi-scale urban terrain stratification data are obtained.

5. The multi-scale slicing method for urban waterlogging simulation according to claim 1, characterized in that: Based on the multi-scale urban terrain layered data, the water flow velocity, drainage system capacity and land water absorption rate of the differentiated areas are analyzed, the drainage capacity index of the differentiated areas is calculated, and the steps of obtaining the hydrological parameter analysis results are specifically as follows: Based on the multi-scale urban terrain layered data, each region is analyzed to extract the terrain information and land use characteristics of the region, identify the water flow path and the location of the drainage system, and classify the drainage characteristics to obtain differentiated regional drainage basic data; Based on the differentiated regional drainage basic data, the water flow velocity of each region is calculated, and the water flow rate of each region and the drainage velocity of the drainage system are measured in combination with the terrain height, slope and the capacity of the current drainage system, and the land water absorption capacity of the differentiated plots is calculated to obtain the differentiated regional hydrological parameters; Based on the differentiated regional hydrological parameters, the water flow velocity, drainage capacity and land water absorption rate parameters of each region are integrated, and the drainage capacity index of each region is calculated using a weighted multi-factor integrated analysis method to obtain the hydrological parameter analysis results.

6. The multi-scale slicing method for urban waterlogging simulation according to claim 5, characterized in that: The weighted multi-factor integrated analysis method is based on the formula: Calculate the differential regional drainage capacity index, where V represents the water flow velocity, C represents the drainage system capacity, S represents the land water absorption rate, and w V 、w C and w S are the weight coefficients of water flow velocity, drainage system capacity and land water absorption rate, and DI is the drainage capacity index.

7. The multi-scale slicing method for urban waterlogging simulation according to claim 1, characterized in that: Based on the hydrological parameter analysis results, the preset values ​​of water flow velocity and drainage system capacity are adjusted to match future engineering changes, and the steps of obtaining adjusted hydrological simulation parameters are as follows: Based on the hydrological parameter analysis results, drainage project data of differentiated areas are extracted, construction progress, construction speed and construction target data of the drainage project are obtained, and drainage project related data are obtained; Based on the drainage project related data, calculate the construction progress of the target period, analyze the impact of the drainage project on the water flow velocity and drainage system capacity during the target period, and obtain the project impact data; Based on the engineering impact data, the drainage capacity of each area is re-evaluated, and the water flow velocity and drainage system capacity parameters of the target period are adjusted to match the drainage engineering impact of the target period to obtain adjusted hydrological simulation parameters.

8. The multi-scale slicing method for urban waterlogging simulation according to claim 1, characterized in that: Based on the adjusted hydrological simulation parameters, the water flow dynamics under differentiated rainfall scenarios are simulated, the water depth of each area is predicted, and the potential waterlogging risk areas are identified. The specific steps for obtaining waterlogging risk prediction information are as follows: Based on the adjusted hydrological simulation parameters, the rainfall scenario of the target area is input, the rainfall amount and rainfall duration of the area are set as differentiated scenarios, water flow simulation is performed, and water flow dynamic data under differentiated rainfall scenarios is obtained; Based on the water flow dynamic data under the differentiated rainfall scenarios, combined with the terrain height and the efficiency of the drainage system, the water depth of each area under the target rainfall scenario is calculated to obtain regional water depth data; Based on the regional waterlogging depth data, a regional risk assessment model is used to analyze the waterlogging risk areas. By comparing the difference between the waterlogging depth and the regional drainage capacity, the risk areas with severe waterlogging are identified and waterlogging risk prediction information is obtained.

9. The multi-scale slicing method for urban waterlogging simulation according to claim 8, characterized in that: The regional risk assessment model is based on the formula: Calculate the waterlogging risk index RI A , where D A Represents the actual water depth, C A represents the regional drainage capacity, λ is the stability constant, K is the adjustment coefficient of the risk index, RI A It is the waterlogging risk index.

10. The multi-scale slicing method for urban waterlogging simulation according to claim 1, characterized in that: Based on the waterlogging risk prediction information, the existing urban planning and infrastructure layout are analyzed, the deficiencies of the current drainage system are identified, urban planning and infrastructure optimization measures are formulated, and the steps for obtaining urban planning adjustment suggestion information are as follows: Based on the waterlogging risk prediction information, the current urban planning layout is analyzed, the risk area is compared with the current urban drainage system layout, the deficiencies and potential weaknesses of the drainage system are identified, and the drainage system deficiency analysis results are obtained; Based on the analysis results of the drainage system deficiency, the current urban infrastructure layout is evaluated, and the key areas and transformation directions of infrastructure optimization are identified by combining the risk areas and drainage system information to obtain infrastructure optimization information; Based on the infrastructure optimization information, combined with the city's planning and development goals, the overall urban planning layout is adjusted, and urban planning optimization measures are formulated, including drainage system expansion and development restrictions in sensitive areas, to obtain urban planning adjustment recommendation information.

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