Urban waterlogging simulation multi-scale slicing method

Abstract

The present application relates to the technical field of urban waterlogging, specifically to a city waterlogging simulation multi-scale slicing method, comprising the following steps: collecting city terrain and land use data based on city remote sensing and geographic information data, performing data cleaning, and uniformly processing the formats of differentiated data sources to obtain a cleaned data set. In the present application, the city is classified according to terrain features and land use by using city remote sensing and geographic information data, and regional slicing is performed in combination with a geographic information system, so that the hydrological model can more accurately reflect the specific conditions of each region, the hydrological parameters can be adjusted according to the specific conditions of different regions, the prediction model can better adapt to future environmental changes, the water flow dynamics under differentiated rainfall scenarios can be simulated, and the waterlogging depth of each region can be predicted, so that potential waterlogging risk areas can be effectively identified, and strong decision support is provided for city planning and infrastructure optimization.

Description

Technical Field

[0001] This invention relates to the field of urban flooding technology, and more particularly to a multi-scale slicing method for simulating urban flooding. Background Technology

[0002] The field of urban flooding technology involves the interdisciplinary application of multiple disciplines, including hydrology, water resource management, urban planning, and disaster prevention. Its main objective is to study and solve urban flooding problems caused by inadequate surface drainage, insufficient sewer system capacity, or over-development during extreme rainfall events. Technologies employed in this field include rainfall simulation, drainage system modeling, topographic and geomorphological analysis, and emergency response plan design. Through in-depth research into the mechanisms of urban flooding, effective prediction and management tools are developed to mitigate the impact of flooding events on the urban environment and residents' lives.

[0003] Among them, the multi-scale slicing method for urban flooding simulation is a technical means for urban flooding risk analysis and management. It creates multi-level models by meticulously slicing urban drainage systems and topography at different scales. This method can simulate water flow dynamics and water accumulation at various scales under different rainfall conditions, thereby identifying potential risk areas and weak points. Its main applications include providing a scientific basis for urban planning and renovation, helping decision-makers develop more effective drainage facility layouts and emergency plans to improve the city's ability to respond to sudden rainfall events and mitigate potential property and life losses.

[0004] Traditional methods for addressing urban flooding caused by extreme rainfall events lack sufficient data integration capabilities and refined analysis of topographic and land use data. The drainage system modeling in traditional methods fails to adequately consider the diversity and complexity of topography, resulting in an inability to accurately predict and manage flooding risks in practical applications. Furthermore, traditional methods have limited ability to adjust hydrological parameters to adapt to future engineering changes. This leads to urban drainage system design and planning being unable to quickly adapt to environmental changes or new urban development needs, increasing the risk of urban disasters under extreme weather conditions. The lack of flexible adjustment of hydrological model parameters limits the speed and efficiency of urban response to sudden flood events. Summary of the Invention

[0005] The purpose of this invention is to address the shortcomings of existing technologies by proposing a multi-scale slicing method for simulating urban flooding.

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

[0007] S1: Based on urban remote sensing and geographic information data, collect urban topography and land use data, clean the data, unify the format of different data sources, and obtain the cleaned dataset.

[0008] S2: Based on the cleaned dataset, combined with the geographic information system, the dataset is sliced ​​into regions, and cities are classified according to topographic features and land use differences to obtain multi-scale urban topographic stratification data;

[0009] S3: Based on the multi-scale urban topographic stratification data, analyze the water flow velocity, drainage system capacity and land water absorption rate of the differentiated areas, calculate the drainage capacity index of the differentiated areas, and obtain the 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 the 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 region, identify potential waterlogging risk areas, and obtain waterlogging risk prediction information.

[0012] S6: Based on the aforementioned urban flooding 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 suggestions.

[0013] As a further aspect of the present invention, the cleaned dataset includes standardized topographic elevation data, land use classification data, and supplemented remote sensing image data. The multi-scale urban topographic stratification data includes the region's basic hydrological sensitivity rating, regional boundary definition, and land use type. The hydrological parameter analysis results include water flow velocity, drainage capacity index, and land water absorption data for each region. The adjusted hydrological simulation parameters include adjusted water flow velocity parameters and drainage capacity parameters. The urban flooding risk prediction information includes the urban flooding risk level, predicted water depth, and location of urban flooding for each region. The urban planning adjustment suggestion information includes drainage system improvement measures, land use adjustment suggestions, and locations of flood control measures.

[0014] As a further aspect of the present invention, the steps of collecting urban topography and land use data based on urban remote sensing and geographic information data, cleaning the data, unifying the formats of differentiated data sources, and obtaining the cleaned dataset are as follows:

[0015] S101: Based on urban 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 urban terrain data.

[0016] S102: Based on the initial screening of urban terrain data, outlier removal is performed. Data that exceeds the reasonable range in elevation and slope data is reviewed, and abnormal data is excluded. Missing data is then filled in by interpolation estimation to optimize the continuity of terrain data and obtain the completed data.

[0017] S103: Based on the completed data, perform unified processing on the data from different sources, including adjusting the coordinate system, resolution and data format, optimizing the consistency and usability of the data, and obtaining the cleaned dataset.

[0018] As a further aspect of the present invention, based on the cleaned dataset and combined with a geographic information system, the dataset is regionally sliced, and cities are classified according to topographic features and land use differences to obtain multi-scale urban topographic stratification data. The specific steps are as follows:

[0019] S201: Based on the cleaned dataset, the city area is segmented according to a preset spatial grid using a geographic information system, the boundaries and characteristics of the differentiated areas are identified, and the city is divided into multiple geographic units to obtain urban area slice data.

[0020] S202: Based on the urban area slice data, the terrain of each geographic unit is classified, and the elevation, slope change and river distribution in the differentiated units are identified and divided. The terrain feature data is then matched with the geographic units to obtain terrain feature classification data.

[0021] S203: Based on the topographic feature classification data, combined with regional waterlogging records and land use records, the waterlogging risk of differentiated areas is assessed according to the regional topography and land use to obtain multi-scale urban topographic stratification data.

[0022] As a further aspect of the present invention, based on the multi-scale urban topographic stratification data, the steps for analyzing the water flow velocity, drainage system capacity, and land water absorption rate of differentiated areas, calculating the drainage capacity index of differentiated areas, and obtaining the hydrological parameter analysis results are as follows:

[0023] S301: Based on the multi-scale urban topographic layered data, analyze each region, extract the region's topographic information and land use characteristics, identify the location of water flow paths and drainage systems, and classify drainage characteristics to obtain differentiated regional drainage basic data.

[0024] S302: Based on the basic data of drainage in the differentiated areas, the water flow velocity of each area is calculated. Combining the terrain elevation, slope and the capacity of the current drainage system, the water flow rate and drainage velocity of the drainage system in each area are measured, and the water absorption capacity of the differentiated plots is calculated to obtain the hydrological parameters of the differentiated areas.

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

[0026] As a further aspect of the present invention, the weighted multi-factor integration analysis method is based on the formula:

[0027]

[0028] Calculate the drainage capacity index for differentiated areas, 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 These are the weighting coefficients for water flow velocity, drainage system capacity, and land water absorption rate, respectively, with DI being the drainage capacity index.

[0029] As a further aspect of the present invention, the specific steps for adjusting the preset values ​​of water flow velocity and drainage system capacity based on the hydrological parameter analysis results, and matching future engineering changes, to obtain the adjusted hydrological simulation parameters are as follows:

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

[0031] S402: Based on the drainage project correlation data, calculate the construction progress for the target time period, analyze the impact of the drainage project on the water flow velocity and drainage system capacity during the target time period, and obtain the project impact data;

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

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

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

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

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

[0037] As a further aspect of the present invention, the regional risk assessment model is based on the formula:

[0038]

[0039] Calculate the waterlogging risk index RI A , where D A C represents the actual water depth. A RI represents the drainage capacity of the region, λ is a stability constant, K is an adjustment coefficient for the risk index. A This is the urban flooding risk index.

[0040] As a further aspect of the present invention, the steps of analyzing existing urban planning and infrastructure layout based on the aforementioned urban flooding risk prediction information, identifying deficiencies in the current drainage system, formulating urban planning and infrastructure optimization measures, and obtaining urban planning adjustment suggestions are as follows:

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

[0042] S602: Based on the analysis results of the drainage system deficiencies, assess the current urban infrastructure layout, and combine risk areas and drainage system information to identify key areas and directions for infrastructure optimization and obtain infrastructure optimization information;

[0043] S603: Based on the infrastructure optimization information and in conjunction with the city's planning and development goals, adjust the overall urban planning layout, formulate urban planning optimization measures, including drainage system expansion and development restrictions in sensitive areas, and obtain urban planning adjustment suggestions.

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

[0045] This invention utilizes urban remote sensing and geographic information data to collect and integrate urban topography and land use data, enhancing the accuracy and application scope of the dataset. Cities are classified according to topographic features and land use, and regional slicing is performed using a geographic information system, enabling the hydrological model to more accurately reflect the specific conditions of each region. This improves the model's practical application value and prediction accuracy. Through the analysis of multi-scale urban topographic stratified data, hydrological parameters can be adjusted for the specific conditions of different regions, allowing the prediction model to better adapt to future environmental changes. It simulates water flow dynamics under differentiated rainfall scenarios and predicts the water depth in each region, effectively identifying potential urban flooding risk areas. This provides strong decision support for urban planning and infrastructure optimization, enhances the ability to respond to sudden rainfall events, and helps mitigate potential property and life losses. Attached Figure Description

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

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

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

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

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

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

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

[0053] To make the objectives, technical solutions, and advantages of this invention clearer, the 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 merely illustrative and not intended to limit the invention.

[0054] In the description of this invention, it should be understood that the terms "length," "width," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," and "outer," etc., indicating orientation or positional relationships, are based on the orientation or positional relationships shown in the accompanying drawings and are only for the convenience of describing the invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of the invention. Furthermore, in the description of this invention, "a plurality of" means two or more, unless otherwise explicitly specified.

[0055] Please see Figure 1 This invention provides a technical solution: a multi-scale slicing method for simulating urban flooding, comprising the following steps:

[0056] S1: Based on urban remote sensing and geographic information data, urban topography and land use data are collected, remote sensing images are integrated, data is cleaned, outliers are removed and missing values ​​are filled, and the formats of different data sources are uniformly processed to obtain the 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 topographic features and land use differences to obtain multi-scale urban topographic stratification data.

[0058] S3: Based on multi-scale urban topographic stratification data, the flow velocity, drainage system capacity and land water absorption rate of differentiated areas are analyzed, drainage capacity indicators of differentiated areas are calculated, and data are integrated to obtain hydrological parameter analysis results.

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

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

[0061] S6: Based on urban flooding 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 suggestions.

[0062] The cleaned dataset includes standardized topographic elevation data, land use classification data, and completed remote sensing imagery data. Multi-scale urban topographic stratification data includes basic hydrological sensitivity ratings, regional boundary definitions, and land use types. Hydrological parameter analysis results include water flow velocity, drainage capacity indicators, and land absorbency data for each region. Adjusted hydrological simulation parameters include adjusted water flow velocity and drainage capacity parameters. Urban flooding risk prediction information includes the urban flooding risk level, predicted water depth, and location of urban flooding for each region. Urban planning adjustment recommendations include drainage system improvement measures, land use adjustment recommendations, and locations of flood control measures.

[0063] Please see Figure 2 Based on urban remote sensing and geographic information data, urban topography and land use data are collected, remote sensing images are integrated, data cleaning is performed, outliers are removed and missing values ​​are filled, and the formats of different data sources are standardized to obtain the cleaned dataset. The specific steps are as follows:

[0064] S101: Based on urban 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 urban terrain data.

[0065] Based on urban remote sensing and geographic information data, urban topographic data was collected. Elevation information was extracted from multi-source remote sensing data, and a digital elevation model (DEM) was used to analyze the elevation value, slope change, and surface features of each data point. Each data point was extracted item by item, and slope was calculated using topographic analysis tools. A surface feature classification algorithm was used to distinguish different landform types. By setting elevation error thresholds and slope change thresholds, data points exceeding the error range were removed. For example, data points with elevation errors exceeding ±3 meters or slope abrupt changes exceeding 45 degrees were identified as erroneous and removed, resulting in a pre-screened urban topographic dataset that eliminated obvious erroneous elevations and unreasonable slope changes.

[0066] S102: Based on the initial screening of urban terrain data, outlier removal is performed. Data that exceeds the reasonable range in elevation and slope data is reviewed, and outlier data is excluded. Missing data is then filled in through interpolation estimation to optimize the continuity of terrain data and obtain the completed data.

[0067] Based on the initial screening of urban topographic data, outlier removal was performed. Reasonable data ranges were established; for example, elevation data should fall between the known highest and lowest points of the city, and slope should not exceed the natural terrain's maximum slope. Data points exceeding these reasonable ranges in elevation and slope were reviewed, and box plot methods were used to identify and eliminate outliers. For missing elevation or slope information, spatial interpolation methods such as Kriging interpolation were used to estimate the missing data, optimizing data continuity and completeness to obtain the supplemented data.

[0068] S103: Based on the completed data, perform unified processing on data from different sources, including adjusting the coordinate system, resolution, and data format, optimizing data consistency and usability, and obtaining a cleaned dataset.

[0069] Based on the completed data, data from different sources are processed uniformly, and the coordinate systems of each data source are adjusted to a unified geographic coordinate system to ensure spatial consistency of all data. The resolution of the data is unified by upsampling low-resolution data and downsampling high-resolution data to match the standard resolution required by the project. Data of different formats are converted into a unified format, such as from Shapefile to GeoJSON, to ensure data availability and compatibility, resulting in a cleaned dataset.

[0070] Please see Figure 3 Based on the cleaned dataset, and in conjunction with a geographic information system, the dataset is regionally sliced, and cities are classified according to topographic features and land use differences to obtain multi-scale urban topographic stratification data. The specific steps are as follows:

[0071] S201: Based on the cleaned dataset, the urban area is segmented according to a preset spatial grid using a geographic information system, the boundaries and characteristics of the 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 divide the city into regions by setting a grid resolution, such as 50 meters x 50 meters per grid. By comparing topographic elevations 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 regions were then labeled, and the city was divided into different geographic units based on these boundaries, each unit representing a type of topographic or land cover feature. This process ensured that the topographic features within each geographic unit were relatively consistent, while maintaining clear distinctions from adjacent units, resulting in urban area slice data.

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

[0074] Based on urban area slice data, detailed terrain classification is performed for each geographic unit. Using terrain analysis tools, statistical analysis is conducted on the elevation and slope data of each unit to identify the main topographic trends and analyze the distribution of rivers within each unit, including river length, flow direction, and relative position to the terrain. Terrain features are then linked to each geographic unit through a geographic information system (GIS) to construct a comprehensive terrain feature classification dataset that includes terrain categories (e.g., plains, hills, mountains) and river distribution. This dataset provides a detailed description of the natural geographic characteristics of each geographic unit, offering a necessary foundation for terrain-related risk analysis.

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

[0076] Based on topographic feature classification data, combined with regional waterlogging records and land use records, the waterlogging risk of each region is assessed. The analysis of land use types within the region, such as residential areas, industrial areas, or farmland, reveals that each land use type has different hydrological impact characteristics, affecting surface water discharge and infiltration. Combining topographic data, particularly slope and river distribution, hydrological models are used to calculate the potential water accumulation depth and flow direction for each region under extreme rainfall events. Through analysis, the waterlogging risk level of the region is quantitatively assessed, resulting in a stratified urban topographic risk dataset encompassing multiple scales and levels, which identifies potential risk areas.

[0077] Please see Figure 4 Based on multi-scale urban topographic stratification data, this study analyzes the water flow velocity, drainage system capacity, and land water absorption rate in differentiated areas, calculates the drainage capacity index of these differentiated areas, and integrates the data to obtain the hydrological parameter analysis results. The specific steps are as follows:

[0078] S301: Based on multi-scale urban topographic stratification data, each region is analyzed to extract topographic information and land use characteristics, identify the location of water flow paths and drainage systems, and classify drainage characteristics to obtain differentiated regional drainage basic data.

[0079] Based on multi-scale urban topographic stratification data, the topographic and land use characteristics of each region are meticulously extracted. Digital elevation models (DEMs) are used to determine the elevation and slope information of the regions, and land cover data is combined to identify various land uses, such as residential areas, commercial areas, or public facility areas. Geographic information systems (GIS) are used to analyze water flow paths and identify the locations of natural and artificial drainage systems, such as rivers, ditches, and sewer systems. Drainage characteristics are categorized for different types of drainage facilities, considering their design capacity and actual operational efficiency, and integrated to form differentiated regional drainage baseline data, marking the drainage characteristics of each region, including water flow paths, drainage facility types, and status.

[0080] S302: Based on the basic data of drainage in different regions, the water flow velocity of each region is calculated. Combining the terrain elevation, slope and the capacity of the current drainage system, the water flow and drainage velocity of the drainage system in each region are measured, and the water absorption capacity of the land in different plots is calculated to obtain the hydrological parameters of the different regions.

[0081] When calculating the water flow velocity for each region based on differentiated regional drainage baseline data, the water flow rate Q is calculated according to the formula: Q=A·V, taking into account the terrain elevation and slope.

[0082] In the formula, Q represents the water flow rate, A represents the cross-sectional area, and V represents the water flow velocity.

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

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

[0085] Q = 10m 2 ×2m / s=20m 3 / s

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

[0087] When calculating the water absorption capacity of the land in each region, the land type and terrain slope are taken into account, and the land water absorption rate S is calculated according to the formula: S=P·(1-I).

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

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

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

[0091] S = 30 mm / h · (1 - 0.2) = 24 mm / h

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

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

[0094] The weighted multifactor integration analysis method, according to the formula:

[0095]

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

[0097] formula:

[0098]

[0099] Parameter details and acquisition methods:

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

[0101] Drainage system capacity C: This represents the maximum volume of water flow that the drainage system can handle per unit time. It is usually obtained from technical data provided by urban planning departments or water bureaus, or calculated from drainage system design parameters.

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

[0103] Weighting coefficient w V w C and w S The coefficients are derived from historical data analysis and expert evaluation, reflecting the relative importance of each parameter in assessing the system's drainage capacity. These weights are determined on a site-specific basis, typically by urban planning departments or water conservancy engineering expert groups based on specific geographical and climatic conditions.

[0104] Calculation example:

[0105] Set the following parameter values:

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

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

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

[0109] Weighting 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, under the given conditions, the area has a fairly high drainage efficiency, sufficient to handle common rainfall events. This indicator helps urban planners and engineers understand the drainage capacity of a specific area and make appropriate infrastructure plans or adjustments accordingly.

[0113] Please see Figure 5 Based on the hydrological parameter analysis results and combined with drainage engineering data, the hydrological parameters are adjusted, including the preset values ​​of water flow velocity and drainage system capacity, to match future engineering 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 engineering data for differentiated areas, obtain data on the construction progress, construction speed, and construction targets of drainage engineering projects, and obtain related data on drainage engineering projects;

[0115] Based on hydrological parameter analysis, relevant data on drainage projects for each region were extracted. This includes specific construction progress data, such as the length of completed pipe networks, the number of installed pumping stations, and the completed drainage ditches. Construction speed data, spanning from project initiation to the present, records the monthly work rate of the construction team, including the daily completed work area and the main construction equipment used. Construction target data is set according to the project plan and urban drainage needs, clearly defining specific target values ​​for improving drainage capacity. Through data collection and integration, a comprehensive drainage project dataset containing construction progress, speed, and targets is formed.

[0116] S402: Based on the associated data of drainage projects, calculate the construction progress for the target period, analyze the impact of drainage projects on 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, and the construction speed v s Given the time increment Δt, the construction progress for the future target period can be calculated using the formula: P t =P0+v s ·Δt.

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

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

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

[0121] P t =30% + 0.5% × 10 = 35%

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

[0123] To analyze the impact of drainage projects on the drainage system capacity during the target time period, the formula C needs to be used. t =C0+

[0124] ΔC. The calculation of ΔC depends on the construction progress P. tFor example, a 1% increase in construction progress can increase drainage capacity by 10 cubic meters relative to changes in P0.

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

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

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

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

[0129] Therefore, after construction is completed, the total capacity of the drainage system will increase to:

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

[0131] The construction project will increase the total capacity of the drainage system to 1050 cubic meters.

[0132] S403: Based on engineering impact data, the drainage capacity of each area is reassessed, and the water flow velocity and drainage system capacity parameters for the target time period are adjusted to match the drainage engineering impact for the target time period, resulting in adjusted hydrological simulation parameters.

[0133] Based on engineering impact data, the drainage capacity of each area was reassessed, and the flow velocity parameters and drainage system capacity parameters were adjusted accordingly. Considering the possibility of partial system malfunction or capacity reduction during construction, hydrological simulation software was used to simulate the adjusted flow and drainage conditions. Taking into account the specific topography and land use of each area, the drainage capacity of each area during construction was reassessed, with a focus on analyzing areas experiencing problems. Through assessment and adjustment, adjusted hydrological simulation parameters were developed. These parameters more accurately reflect the drainage status and corresponding countermeasures in each area under the influence of drainage engineering construction, ensuring the efficiency and safety of the urban drainage system.

[0134] Please see Figure 6 Based on adjusted hydrological simulation parameters, the dynamics of water flow under differentiated rainfall scenarios are simulated to predict the water depth in each region. The simulation results are analyzed to identify potential waterlogging risk areas, and the specific steps for obtaining waterlogging risk prediction information are as follows:

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

[0136] Based on adjusted hydrological simulation parameters, rainfall scenarios are set for the target area. Differentiated rainfall scenarios are established according to historical meteorological data and forecasting models, such as setting rainfall amounts and durations for different regions based on their geographical and climatic characteristics. Hydrological simulation software is used to input rainfall parameters and run models to simulate the impact of rainfall events on the urban drainage system. This simulation yields dynamic water flow data for each region under the set rainfall scenarios, such as flow velocity, flow direction, and potential flooding areas. The data helps to understand the response of the urban drainage system and potential dynamic changes in water flow under specific rainfall conditions.

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

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

[0139] In the formula, R A T represents rainfall intensity. A Q represents the duration of rainfall. A A represents the drainage volume of the drainage system. S The surface representing the region.

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

[0141] Rainfall intensity R A and duration of rainfall T A This information can be obtained from meteorological data and is usually determined based on forecasts or historical data. The drainage capacity Q of the drainage system. A This data is based on actual data obtained from drainage system design and maintenance records. Area surface area A S This information is typically obtained through geographic information systems or on-site measurements.

[0142] Calculation example:

[0143] Set the following parameter value: R A =20 mm / hour (higher rainfall intensity), T A = 3 hours (duration of the rainfall event), 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 indicates that slight waterlogging is expected in the area. While the drainage system is performing well, it may still face challenges under extreme rainfall conditions. The results can help city planners and emergency management departments assess the efficiency of existing drainage facilities and consider whether improvements or expansions are needed to better cope with potential future high-intensity rainfall events.

[0147] S503: Based on regional water depth data, a regional risk assessment model is used to analyze areas at risk of urban flooding. By comparing the difference between water depth and regional drainage capacity, areas at risk of severe water accumulation are identified, and urban flooding risk prediction information is obtained.

[0148] The regional risk assessment model is based on the formula:

[0149]

[0150] Calculate the waterlogging risk index RI A , where D A C represents the actual water depth. A λ represents the area's drainage capacity, i.e., the maximum drainage volume designed for the area; λ is a stability constant used to ensure the denominator is non-zero; K is an adjustment coefficient for the risk index to increase the sensitivity of the calculation results; RI A This is the urban flooding risk index.

[0151] formula:

[0152]

[0153] Parameter details and acquisition methods:

[0154] D A Actual water depth, usually obtained through on-site measurement or estimation using rainfall models, is measured in meters. This is data obtained through direct observation or calculation, reflecting the water accumulation situation in the area after a specific rainfall event.

[0155] C A Regional drainage capacity is data obtained from drainage system design documents or calculations using hydraulic models, representing the maximum water volume that the drainage system can handle under design conditions.

[0156] λ: This is a small positive number added to ensure computational stability. It is usually set to 0.1 to avoid the case where the denominator is zero.

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

[0158] Calculation example:

[0159] The specific parameters of the design are as follows:

[0160] D A =0.5 meters, representing the depth of water accumulation observed in a certain area after a relatively heavy rainfall event.

[0161] C A =0.3 meters, which represents 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, then adjust with a positive number:

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

[0165]

[0166] Calculate the risk index:

[0167]

[0168] Calculation result RI A =124.7 indicates that, given that the water depth is much greater than the design capacity of the drainage system, the risk of flooding in this area is very high. 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] Please see Figure 7 Based on urban flooding risk prediction information, the steps involved in analyzing existing urban planning and infrastructure layout, identifying deficiencies in the current drainage system, formulating urban planning and infrastructure optimization measures, and obtaining urban planning adjustment recommendations are as follows:

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

[0171] Based on urban flooding risk prediction information, the current urban planning layout is analyzed. A geographic information system (GIS) is used to overlay maps of flooding risk areas onto the existing urban drainage system layout map to identify which areas have the closest locational relationship between drainage facilities and risk areas. The design capacity, service life, and most recent maintenance status of the regional drainage system are analyzed to identify deficiencies and potential weaknesses in the drainage system, such as insufficient drainage pipe diameter, outdated drainage grids, or improper maintenance. The information is then integrated to obtain the results of the drainage system deficiency analysis.

[0172] S602: Based on the analysis results of the inadequacy of the drainage system, assess 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 analysis of drainage system deficiencies, the current urban infrastructure layout is assessed. Special attention is paid to areas with insufficient drainage capacity and high risk, evaluating the service provided by existing infrastructure to these areas. Considering the impact of inadequate drainage on urban functions and residents' lives, key areas for infrastructure optimization and directions for improvement are identified. For example, improvement measures such as increasing the density of drainage pipe networks, upgrading aging drainage networks, or adding temporary water storage areas are proposed, thus obtaining information for infrastructure optimization.

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

[0175] Based on infrastructure optimization information and combined with the city's planning and development goals, adjustments are made to the overall urban planning layout. 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. These include expanding drainage systems in high-risk flood areas, increasing green infrastructure such as rain gardens and permeable paving to improve surface moisture infiltration, and restricting development in sensitive areas, such as prohibiting the construction of large commercial centers or residential areas in flood-prone areas. This yields information on suggestions for urban planning adjustments.

[0176] The above are merely preferred embodiments of the present invention and are not intended to limit the present invention in any other way. Any person skilled in the art may make changes or modifications to the above-disclosed technical content to create equivalent embodiments that can be applied to other fields. However, any simple modifications, equivalent changes, and modifications made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the protection scope of the present invention.

Claims

1. A multi-scale slicing method for simulating urban flooding, characterized in that, Includes the following steps: Based on urban remote sensing and geographic information data, urban topography and land use data are collected, cleaned, and the formats of different data sources are standardized to obtain a cleaned dataset. Based on the cleaned dataset, combined with a geographic information system, the dataset is sliced ​​into regions, and cities are classified according to topographic features and land use differences to obtain multi-scale urban topographic stratification data. Based on the multi-scale urban topographic 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, resulting in the adjusted hydrological simulation parameters. Based on the adjusted hydrological simulation parameters, the dynamics of water flow under different rainfall scenarios are simulated to predict the water depth in each region, identify potential waterlogging risk areas, and obtain waterlogging risk prediction information. Based on the aforementioned urban flooding 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 suggestions.

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

3. The multi-scale slicing method for simulating urban flooding according to claim 1, characterized in that, Based on urban remote sensing and geographic information data, the following steps are taken to collect urban topography and land use data, clean the data, and unify the formats of different data sources to obtain the cleaned dataset: Based on 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 one by one. The data is then filtered to remove erroneous elevation and slope information, resulting in preliminary urban terrain data. Based on the initial screening of urban terrain data, outlier removal is performed. Data that exceeds the reasonable range in elevation and slope data is reviewed and outlier data is excluded. Missing data is then filled in by interpolation estimation to optimize the continuity of terrain data and obtain the completed data. Based on the completed data, the data from different sources are processed uniformly, including adjusting the coordinate system, resolution, and data format, to optimize the consistency and usability of the data, resulting in a cleaned dataset.

4. The multi-scale slicing method for simulating urban flooding according to claim 1, characterized in that, Based on the cleaned dataset, and in conjunction with a geographic information system, the dataset is regionally sliced, and cities are classified according to topographic features and land use differences to obtain multi-scale urban topographic stratification data. The specific steps are as follows: Based on the cleaned dataset, the urban area is segmented according to a preset spatial grid using a geographic information system, the boundaries and characteristics of different areas are identified, and the city is divided into multiple geographic units to obtain urban area slice data. Based on the urban area slice data, the terrain of each geographic unit is classified, and the elevation, slope change and river distribution in the differentiated units are identified and divided. The terrain feature data is then matched with the geographic units to obtain terrain feature classification data. Based on the topographic feature classification data, combined with regional waterlogging records and land use records, the waterlogging risk of differentiated areas is assessed according to the regional topography and land use, resulting in multi-scale urban topographic stratification data.

5. The multi-scale slicing method for simulating urban flooding according to claim 1, characterized in that, Based on the aforementioned multi-scale urban topographic stratification data, the steps for analyzing water flow velocity, drainage system capacity, and land water absorption rate in differentiated areas, calculating drainage capacity indices for differentiated areas, and obtaining hydrological parameter analysis results are as follows: Based on the multi-scale urban topographic layered data, each region is analyzed to extract its topographic information and land use characteristics, identify the location of water flow paths and drainage systems, and classify drainage characteristics to obtain differentiated regional drainage basic data. Based on the aforementioned differentiated regional drainage data, the water flow velocity of each region is calculated. Combining the terrain elevation, slope, and current drainage system capacity, the water flow rate and drainage velocity of each region are measured, and the land water absorption capacity of differentiated plots is calculated to obtain the differentiated regional hydrological parameters. Based on the differentiated regional hydrological parameters, the parameters of water flow velocity, drainage capacity and land water absorption rate of each region are integrated, and a weighted multi-factor integrated analysis method is used to calculate the drainage capacity index of each region, thus obtaining the hydrological parameter analysis results.

6. The multi-scale slicing method for simulating urban flooding according to claim 5, characterized in that, The weighted multifactor integration analysis method is based on the formula: Calculate the drainage capacity index for differentiated areas, 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 These are the weighting coefficients for water flow velocity, drainage system capacity, and land water absorption rate, respectively, with DI being the drainage capacity index.

7. The multi-scale slicing method for simulating urban flooding according to claim 1, characterized in that, Based on the hydrological parameter analysis results, the specific steps for adjusting the preset values ​​of water flow velocity and drainage system capacity to match future engineering changes and obtain the adjusted hydrological simulation parameters are as follows: Based on the hydrological parameter analysis results, drainage engineering data for differentiated areas are extracted to obtain data on the construction progress, construction speed, and construction targets of drainage engineering projects, thereby obtaining related data on drainage engineering projects. Based on the drainage project correlation data, the construction progress during the target period is calculated, and the impact of the drainage project on the water flow velocity and drainage system capacity during the target period is analyzed to obtain the project impact data. Based on the engineering impact data, the drainage capacity of each area is reassessed, and the water flow velocity and drainage system capacity parameters for the target time period are adjusted to match the drainage engineering impact for the target time period, resulting in adjusted hydrological simulation parameters.

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

9. The multi-scale slicing method for simulating urban flooding 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 C represents the actual water depth. A RI represents the drainage capacity of the region, λ is a stability constant, K is an adjustment coefficient for the risk index. A This is the urban flooding risk index.

10. The multi-scale slicing method for simulating urban flooding according to claim 1, characterized in that, Based on the aforementioned urban flooding risk prediction information, the specific steps for analyzing existing urban planning and infrastructure layout, identifying deficiencies in the current drainage system, formulating urban planning and infrastructure optimization measures, and obtaining urban planning adjustment recommendations are as follows: Based on the aforementioned urban flooding risk prediction information, the current urban planning layout is analyzed, the risk areas are compared with the current urban drainage system layout, the deficiencies and potential weaknesses of the drainage system are identified, and the results of the drainage system deficiency analysis are obtained. Based on the analysis results of the drainage system deficiencies, the current urban infrastructure layout is assessed. Combining risk areas and drainage system information, key areas for infrastructure optimization and transformation directions are identified, and infrastructure optimization information is obtained. Based on the infrastructure optimization information and in conjunction with the city's planning and development goals, the overall urban planning layout is adjusted, and urban planning optimization measures are formulated, including the expansion of the drainage system and development restrictions in sensitive areas, resulting in suggestions for urban planning adjustments.

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