A multi-scale full-cycle stormwater resilience assessment method, device, medium and product

Abstract

The application discloses a multi-scale full-cycle rain flood resilience evaluation method and device, medium and product, and relates to the field of rain flood resilience evaluation. First, a multi-scale full-cycle rain flood resilience element library is constructed according to the rainstorm flood action cycle and the three spatial scales of a basin-city-drainage partition; each element data in the element layer in the full-cycle process of coping with the rainstorm flood action under the three spatial scales of a basin-city-drainage partition is collected and calculated; the final multi-scale full-cycle rain flood resilience element library is screened based on the correlation between elements; the weight of each element in the final multi-scale full-cycle rain flood resilience element library is calculated by using an entropy weight method; on the basis of weight calculation, the rain flood resilience under each spatial scale is calculated by using a VIKOR multi-criteria decision method, and the most significant elements are analyzed from the aspects of spatial scale and rainstorm flood action stage by using a geographic detector, so that scientific, efficient and accurate evaluation of the multi-scale full-cycle rain flood resilience is realized.

Description

Technical Field

[0001] This application relates to the field of stormwater resilience assessment technology, and in particular to a multi-scale, full-cycle stormwater resilience assessment method, equipment, medium, and product. Background Technology

[0002] Against the backdrop of accelerating global climate change and urbanization, extreme rainstorms are becoming increasingly frequent, and floods have become one of the most severe disasters affecting river basins and cities. From a macro perspective, the topography, river system distribution, and hydrological cycle of a river basin play a fundamental role in the formation and development of floods. From a micro perspective, urban underlying surface conditions, such as land use type, vegetation cover, and the layout and capacity of drainage systems, also profoundly influence the evolution path and severity of floods.

[0003] Quantitative analysis is an important method for assessing stormwater resilience. Currently, the most commonly used methods include index system methods, scenario simulation methods, and complex network models. However, current assessments of stormwater resilience mostly focus on the resilience capacity of a single scale or a single process, and a dynamic assessment method based on the entire life cycle of stormwater and flood effects has not yet been developed, making it impossible to assess stormwater resilience capacity from multiple scales and throughout the entire life cycle. Summary of the Invention

[0004] The purpose of this application is to provide a multi-scale, full-cycle stormwater resilience assessment method, equipment, medium, and product that can scientifically, efficiently, and accurately evaluate stormwater resilience across multiple scales and throughout the entire lifecycle.

[0005] To achieve the above objectives, this application provides the following solution.

[0006] Firstly, this application provides a multi-scale, full-cycle stormwater resilience assessment method, including: Based on the cycle of rainstorm and flood and the three spatial scales of watershed, city and drainage zone, a multi-scale full-cycle rainstorm resilience element database is constructed. The multi-scale full-cycle rainstorm resilience element database includes a target layer, an indicator layer and an element layer, as well as the corresponding action stage and indicator attributes of each element. The action stages of each element include the rainstorm initiation stage, the flood disaster formation stage, the flood disaster duration stage and the flood disaster recovery stage. Collect and calculate the data of each element in the element layer during the entire cycle of responding to rainstorms and floods at three spatial scales: watershed, city, and drainage zone. The final multi-scale, full-cycle stormwater resilience element database was selected based on the correlation between elements. The weight of each element in the final multi-scale, full-cycle stormwater resilience element database is calculated using the entropy weight method. Based on the weighted calculation, the VIKOR multi-criteria decision method is used to calculate the stormwater resilience at each spatial scale, and a geographic detector is used to analyze the most significant factors from two aspects: spatial scale and stormwater flooding stage.

[0007] Optionally, the construction of a multi-scale, full-cycle rainstorm resilience element database based on the rainstorm and flood cycle and the three spatial scales of watershed-city-drainage zone specifically includes: The entire cycle of rainstorm and flood effects is divided into four stages: the rainstorm initiation stage, the flood formation stage, the flood duration stage, and the flood recovery stage. The study area was divided into three spatial scales: watershed, urban area, and drainage zone. A multi-scale, full-cycle stormwater resilience element database is constructed based on the DPSIR framework. The database is divided into three spatial scales: watershed, city, and drainage zone. The target layer of each spatial scale includes five systems: driving force, pressure, state, impact, and response. The driving forces at the watershed scale include two indicator layers: urban expansion and extreme precipitation. Urban expansion corresponds to factors such as land use, population density, the proportion of the aging population, and GDP per capita. Extreme precipitation corresponds to factors such as R20mm, Rx5day, CWD, and SDII. The pressures at the watershed scale include three indicator layers: natural environment, hydrological data, and infrastructure. Natural environment factors include ground elevation, rainwater gradient, ground roughness, and soil permeability. Hydrological data factors include river network density and water connectivity. Infrastructure factors include emergency shelter density, regional road density, regional medical facility density, and regional fire station density. The watershed-scale status includes two aspects: inundation status and water storage capacity. At the indicator level, the elements corresponding to the inundation state include surface runoff and surface inundation area; the elements corresponding to the regulation capacity include green space ratio, reservoir regulation capacity, river regulation capacity, and flood storage area capacity. At the watershed scale, the impacts include three indicator levels: economic impact, rainwater erosion, and affected population. The economic impact corresponds to economic losses; the rainwater erosion corresponds to topographic humidity index and sediment transport index; and the affected population corresponds to the percentage of vulnerable population. At the watershed scale, the response includes three indicator levels: ecosystem service function, financial support, and rainwater monitoring. The ecosystem service function corresponds to climate regulation and water conservation; the financial support corresponds to investment in flood control; and the rainwater monitoring corresponds to a rainwater monitoring system. The driving forces at the urban scale include two indicator layers: urban expansion and extreme precipitation. Urban expansion corresponds to factors such as land use, population density, the proportion of the aging population, and GDP per capita. Extreme precipitation corresponds to factors such as R20mm, Rx5day, CWD, and SDII. The pressures at the urban scale include five indicator layers: natural environment, hydrological data, infrastructure, water conservancy facilities, and urban construction. Natural environment factors include ground elevation, rainwater slope, ground roughness, and soil permeability. Hydrological data factors include water system area and water connectivity. Infrastructure factors include emergency shelter density, regional road density, regional medical facility density, and regional fire station density. Water conservancy facilities factors include dam flood control standards, drainage network density, drainage network diameter, and rainwater storage facility density. Urban construction factors include road width and building density. The city-scale status includes two indicator layers: inundation status and water storage capacity. The inundation status corresponds to the elements of surface runoff and surface inundation range, while the water storage capacity corresponds to the elements of green space ratio, reservoir storage capacity, river storage capacity, and flood detention area capacity. The city-scale impact includes three indicator layers: economic impact, rainwater erosion, and affected population. The economic impact corresponds to the element of economic loss, the rainwater erosion corresponds to the elements of topographic humidity index and sediment transport index, and the affected population corresponds to the element of the percentage of vulnerable population. The city-scale response includes four indicator layers: ecosystem service function, financial support, rainwater monitoring, and blue-green water storage measures. The ecosystem service function corresponds to the elements of climate regulation and water conservation, the financial support corresponds to the element of flood control investment, the rainwater monitoring corresponds to the element of rainwater monitoring system, and the blue-green water storage measures correspond to the element of sponge city facilities. The driving forces at the drainage zoning scale include two indicator layers: urban expansion and extreme precipitation. Urban expansion corresponds to factors such as land use, population density, proportion of aging population, and GDP per capita. Extreme precipitation corresponds to factors such as R20mm, Rx5day, CWD, and SDII. The pressures at the drainage zoning scale include four indicator layers: natural environment, hydrological data, water infrastructure, and urban construction. Natural environment factors include ground elevation, rainwater slope, ground roughness, and soil permeability. Hydrological data corresponds to the area of ​​waterways. Water infrastructure factors include drainage network density, drainage network diameter, and rainwater storage facility density. Urban construction factors include… The elements at the drainage zoning scale include road width and building density; the state at the drainage zoning scale includes two indicator layers: flooding state and storage capacity. The elements corresponding to flooding state include surface runoff and surface flooding range, while the elements corresponding to storage capacity include green space ratio and road connectivity; the impacts at the drainage zoning scale include two indicator layers: rainwater erosion and affected population. The elements corresponding to rainwater erosion include topographic humidity index and sediment transport index, while the elements corresponding to affected population are the percentage of vulnerable population; the response at the drainage zoning scale includes two indicator layers: rainwater monitoring and blue-green storage measures. The element corresponding to rainwater monitoring is the rainwater monitoring system, and the element corresponding to blue-green storage measures is sponge city facilities. Each element corresponds to one or more of the following four stages: the beginning of the rainstorm, the formation of the flood disaster, the duration of the flood disaster, and the recovery stage of the flood disaster; the indicator attribute corresponding to each element is positive or negative.

[0008] Optionally, the division of the study area into three spatial scales—watershed, urban, and drainage zone—specifically includes: The watershed scale to which it belongs is determined based on the regional planning of the study area; Determine the city scale based on the boundaries of the city's administrative regions; Using ArcGIS hydrological analysis tools and the SWAT model, river catchment points and catchment areas are calculated, and watershed hydrological response units are divided accordingly. The hydrological response units are then modified based on the layout of the drainage network to form a research unit range that conforms to the hydrological process and engineering reality as the drainage zoning scale.

[0009] Optionally, the step of filtering the final multi-scale, full-cycle stormwater resilience element database based on the correlation between elements specifically includes: Spearman correlation analysis was used to measure the correlation between elements at each spatial scale in the multi-scale full-cycle stormwater resilience element database. Elements with high correlation were removed, thereby selecting the final multi-scale full-cycle stormwater resilience element database for the corresponding spatial scale.

[0010] Optionally, the calculation of the weight of each element in the final multi-scale, full-cycle stormwater resilience element database using the entropy weight method specifically includes: For each spatial scale of the study area, the data of each element are standardized according to the index attributes of each element in the final multi-scale full-cycle rainwater resilience element database, so as to obtain the index value of each element after standardization. Calculate the information entropy of each element based on the standardized index values ​​of each element's data; The weight of each element is calculated based on its information entropy.

[0011] Optionally, based on the weight calculation, the VIKOR multi-criteria decision method is used to calculate the stormwater resilience at each spatial scale, specifically including: For each spatial scale of the study area, the positive ideal solution and the negative ideal solution are determined based on the standardized index values ​​of each element in the final multi-scale full-cycle rainwater resilience element database. Calculate the group effect value and individual regret value based on the positive and negative ideal solutions; Calculate the benefit ratio based on the group effect value and the individual regret value; Rainwater resilience is calculated based on the benefit ratio.

[0012] Optionally, the use of a geographic detector to analyze the most significant influencing factors from two aspects: spatial scale and the stage of rainstorm and flooding, specifically includes: For each spatial scale of the study area, the elements in the final multi-scale full-cycle rainwater resilience element database are used as independent variables, and the corresponding rainwater resilience is used as the dependent variable. The data are input into the geographic detector model to obtain the significance of each element. Based on the action stage of each element and its significance, the elements with the most significant impact in the four action stages are identified.

[0013] Secondly, this application provides a computer device, including: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the multi-scale full-cycle rainwater resilience assessment method.

[0014] Thirdly, this application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the multi-scale full-cycle stormwater resilience assessment method.

[0015] Fourthly, this application provides a computer program product, including a computer program that, when executed by a processor, implements the multi-scale full-cycle stormwater resilience assessment method.

[0016] Based on the specific embodiments provided in this application, the following technical effects are disclosed.

[0017] This application provides a multi-scale, full-cycle stormwater resilience assessment method, equipment, medium, and product. It divides the stormwater flood cycle into four stages: storm onset, flood formation, flood duration, and flood recovery. Following fundamental resilience principles and the stormwater flood inundation evolution mechanism, it constructs stormwater resilience element databases at the watershed, urban, and drainage zone scales based on the DSPIR framework, starting from these four stages. Entropy weighting is used to determine element weights, and the resilience capacity to cope with stormwater floods at the watershed, urban, and drainage zone scales is assessed, forming a multi-scale spatiotemporal distribution pattern of stormwater resilience. Based on stormwater resilience simulation from a full-cycle perspective, the most significant influencing factors at different stormwater flood stages are identified. This application overcomes the limitations of existing research focusing on a single scale, achieving a scientific, efficient, and accurate multi-scale, full-cycle evaluation of stormwater resilience, and can provide scientific guidance for optimizing multi-scale, full-cycle stormwater resilience. Attached Figure Description

[0018] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 This is a flowchart illustrating a multi-scale, full-cycle stormwater resilience assessment method according to this application. Figure 2 This is a closed-loop feedback system diagram of the five systems in the DPSIR framework: driving force, pressure, state, influence, and response. Detailed Implementation

[0020] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0021] This application proposes a multi-scale, full-cycle stormwater resilience assessment method, equipment, medium, and product. By analyzing the stormwater and flood cycle into four stages—the storm initiation stage, the flood formation stage, the flood duration stage, and the flood recovery stage—a stormwater resilience element database at three scales—watershed, city, and drainage zone—is constructed. The method fully considers the dynamic nature and complex interaction of indicators in the stormwater and flood cycle, and assesses stormwater resilience capacity from a multi-scale, full-cycle perspective, providing more scientific, efficient, and accurate technical support for multi-scale stormwater and flood management in watersheds and cities.

[0022] To make the above-mentioned objectives, features and advantages of this application more apparent and understandable, the application will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0023] In one exemplary embodiment, such as Figure 1 As shown, a multi-scale, full-cycle stormwater resilience assessment method is provided, including the following steps 1 to 5.

[0024] Step 1: Construct a multi-scale, full-cycle rainstorm resilience database based on the cycle of rainstorm and flooding and the three spatial scales of watershed, city, and drainage zone.

[0025] The method for constructing the multi-scale, full-cycle rainwater resilience database in this application specifically includes the following steps 1.1 to 1.3.

[0026] Step 1.1: Divide the entire cycle of rainstorm and flood effects into four stages: the rainstorm initiation stage, the flood formation stage, the flood duration stage, and the flood recovery stage.

[0027] The stages of a flood disaster are as follows: The initial stage is the initial rainfall phase, before flooding occurs. The flood formation stage occurs when rainfall exceeds the carrying capacity of the flood storage and drainage systems of the basin, city, and drainage zones, leading to flooding. The flood duration stage occurs after the flood has formed, with continuous heavy rainfall causing ongoing damage to the basin and city, and impacting basic urban operations and the safety of residents' lives and property. The flood recovery stage occurs after the heavy rainfall ends, as the city gradually returns to normal operations from the impact of the floods, and experiences are summarized and policies are updated to cope with future disturbances.

[0028] Step 1.2: Divide the study area into three spatial scales: watershed, city, and drainage zone.

[0029] The study area is divided into watershed, urban, and drainage zone scales to facilitate the subsequent assessment of stormwater resilience at each of the three scales.

[0030] Current research indicates that flood control at a single scale has limitations, and that each scale has its own focus. For example, the watershed level emphasizes the overall regulation of stormwater and floodwater by natural factors and large-scale water conservancy projects; the urban scale focuses on the hydrological response characteristics, land use, and urban infrastructure within the city; and the drainage zoning scale focuses on the operational efficiency and adaptability of the drainage system. The research scope at the watershed-city-drainage zoning scale is gradually narrowing and becoming more focused. The purpose of this application is to assess stormwater resilience at the watershed-city-drainage zoning scales separately, to visualize stormwater resilience at different research scales, and to identify potential risks and weaknesses in stormwater resilience. Therefore, dividing the study area into scales at the geospatial level can lay the foundation for the subsequent assessment of stormwater resilience.

[0031] Step 1.3: Construct a multi-scale, full-cycle rainwater resilience element library based on the DPSIR framework.

[0032] The DPSIR framework comprises five systems: Drive Force, Pressure, State, Impact, and Response. The interactions and feedback between these systems collectively form a closed-loop feedback system for resilience assessment. Figure 2 As shown in Table 1, a multi-scale, full-cycle rainstorm resilience element database was constructed based on the rainstorm and flood cycle and the three spatial scales of watershed-city-drainage zone (hereinafter referred to as scales). In Table 1, T1, T2, T3, and T4 correspond to the rainstorm initiation stage, flood disaster formation stage, flood disaster duration stage, and flood disaster recovery stage, respectively.

[0033] Table 1 Multi-scale, full-cycle rainfall and flood resilience database

[0034] Table 1 shows a multi-scale, full-cycle stormwater resilience database, which includes a target layer, an indicator layer, and an element layer. It also includes the corresponding action stages (T1, T2, T3, T4) and indicator attributes (positive and negative) for each element. The target layer at the three spatial scales of watershed, city, and drainage zone all include five systems: driving force, pressure, state, impact, and response.

[0035] The driving forces at the watershed scale include two indicator layers: urban expansion and extreme precipitation. Urban expansion corresponds to factors such as land use, population density, the proportion of the aging population, and GDP per capita. Extreme precipitation corresponds to factors such as R20mm, Rx5day, CWD, and SDII. The pressures at the watershed scale include three indicator layers: natural environment, hydrological data, and infrastructure. Natural environment factors include ground elevation, rainwater gradient, ground roughness, and soil permeability. Hydrological data factors include river network density and water connectivity. Infrastructure factors include emergency shelter density, regional road density, regional medical facility density, and regional fire station density. The watershed-scale status includes two aspects: inundation status and water storage capacity. At the indicator level, the elements corresponding to the inundation state include surface runoff and surface inundation area; the elements corresponding to the regulation capacity include green space ratio, reservoir regulation capacity, river regulation capacity, and flood storage and detention area capacity. At the watershed scale, the impacts include three indicator levels: economic impact, rainwater erosion, and affected population. The economic impact corresponds to economic losses; the rainwater erosion corresponds to topographic humidity index and sediment transport index; and the affected population corresponds to the percentage of vulnerable population. At the watershed scale, the response includes three indicator levels: ecosystem service function, financial support, and rainwater monitoring. The ecosystem service function corresponds to climate regulation and water conservation; the financial support corresponds to investment in flood control; and the rainwater monitoring corresponds to a rainwater monitoring system.

[0036] The driving forces at the urban scale include two indicator layers: urban expansion and extreme precipitation. Urban expansion corresponds to factors such as land use, population density, the proportion of the aging population, and GDP per capita. Extreme precipitation corresponds to factors such as R20mm, Rx5day, CWD, and SDII. The pressures at the urban scale include five indicator layers: natural environment, hydrological data, infrastructure, water conservancy facilities, and urban construction. Natural environment factors include ground elevation, rainwater slope, ground roughness, and soil permeability. Hydrological data factors include water system area and water connectivity. Infrastructure factors include emergency shelter density, regional road density, regional medical facility density, and regional fire station density. Water conservancy facilities factors include dam flood control standards, drainage network density, drainage network diameter, and rainwater storage facility density. Urban construction factors include road width and building density. The city-scale status includes two indicator layers: inundation status and water storage capacity. The inundation status corresponds to the elements of surface runoff and surface inundation range, while the water storage capacity corresponds to the elements of green space ratio, reservoir storage capacity, river storage capacity, and flood detention area capacity. The city-scale impact includes three indicator layers: economic impact, rainwater erosion, and affected population. The economic impact corresponds to the element of economic loss, the rainwater erosion corresponds to the elements of topographic humidity index and sediment transport index, and the affected population corresponds to the element of the percentage of vulnerable population. The city-scale response includes four indicator layers: ecosystem service function, financial support, rainwater monitoring, and blue-green water storage measures. The ecosystem service function corresponds to the elements of climate regulation and water conservation, the financial support corresponds to the element of flood control investment, the rainwater monitoring corresponds to the element of rainwater monitoring system, and the blue-green water storage measures correspond to the element of sponge city facilities.

[0037] The driving forces at the drainage zoning scale include two indicator layers: urban expansion and extreme precipitation. Urban expansion corresponds to factors such as land use, population density, proportion of aging population, and GDP per capita. Extreme precipitation corresponds to factors such as R20mm, Rx5day, CWD, and SDII. The pressures at the drainage zoning scale include four indicator layers: natural environment, hydrological data, water infrastructure, and urban construction. Natural environment factors include ground elevation, rainwater slope, ground roughness, and soil permeability. Hydrological data corresponds to the area of ​​waterways. Water infrastructure factors include drainage network density, drainage network diameter, and rainwater storage facility density. Urban construction factors include… The elements at the drainage zoning scale include road width and building density; the state at the drainage zoning scale includes two indicator layers: flooding state and storage capacity. The elements corresponding to flooding state include surface runoff and surface flooding range, while the elements corresponding to storage capacity include green space ratio and road connectivity; the impacts at the drainage zoning scale include two indicator layers: rainwater erosion and affected population. The elements corresponding to rainwater erosion include topographic humidity index and sediment transport index, while the elements corresponding to affected population are the percentage of vulnerable population; the response at the drainage zoning scale includes two indicator layers: rainwater monitoring and blue-green storage measures. The element corresponding to rainwater monitoring is the rainwater monitoring system, and the element corresponding to blue-green storage measures is sponge city facilities.

[0038] In the multi-scale, full-cycle rainstorm resilience database (hereinafter referred to as the database), each element (indicator) corresponds to one or more of the following four stages: the initial stage of rainstorm, the formation stage of flood disaster, the duration stage of flood disaster, and the recovery stage of flood disaster; the index attribute of each element (indicator) is either positive or negative.

[0039] Step 2: Collect and calculate the data of each element in the element layer during the entire cycle of responding to rainstorms and floods at three spatial scales: watershed, city, and drainage zone.

[0040] For the study area, based on the multi-scale, full-cycle rainwater resilience element database, data such as geospatial data, hydrological data, meteorological data, and infrastructure data corresponding to each element are collected. For element data that cannot be directly obtained, scientific and effective calculations are performed, and each data is quantified.

[0041] For directly accessible data elements, land use data can be obtained from the National Earth System Science Data Sharing Service Platform. Topographic and geomorphological data can be obtained from the Geospatial Data Cloud Platform. Soil type data can be obtained from the China Soil Data Set of the Harmonized World Soil Database (HWSD). Meteorological data can be obtained from the daily value dataset of China's surface climate data provided by the China Meteorological Data Network. Socioeconomic data can be obtained from the Seventh National Population Census and statistical yearbooks or bulletins of the study area. Water conservancy and hydrological data can be obtained through the study of watershed gate and pumping station observation data, as well as water conservancy project planning and documents. Infrastructure data can be obtained from OpenStreetMap (OSM) public maps and the Gaode POI open platform.

[0042] For example, in Table 1 at the watershed scale, land use data includes land use and green space ratio in the element layer; topographic data includes ground elevation, rainwater slope, and ground roughness in the element layer; socioeconomic data includes population density, proportion of aging population, GDP per capita, economic losses, percentage of vulnerable population, and flood control investment data in the element layer; hydrological data includes river network density, water connectivity, rainwater monitoring system, reservoir storage capacity, river channel storage capacity, and flood storage and detention area capacity data in the element layer; soil type data includes soil permeability in the element layer; meteorological data includes daily precipitation and temperature data for the study area, which prepares for the calculation of R20mm, Rx5day, CWD, and SDII indicators in the subsequent extreme precipitation index layer; and infrastructure data includes elements such as refuge space density, regional road density, regional medical facility density, and regional fire station density.

[0043] At the urban scale, in addition to the above-mentioned elements (indicators), water conservancy and hydrological data include dam flood control standards, drainage network density, and drainage network pipe diameter. Infrastructure data includes road width, building density, and sponge city infrastructure elements.

[0044] The basic data required for drainage zoning have been mentioned above.

[0045] The feature data obtained directly from Table 1 and the feature data calculated later are all raster data, and they are preprocessed in ArcGIS to ensure that the area range, projected coordinate system and resolution are consistent.

[0046] In the feature library shown in Table 1, in addition to the feature data that can be obtained directly, there is also data that needs to be calculated to obtain. The calculation method is described below.

[0047] For example, for extreme precipitation index layer data, it is necessary to construct a daily rainfall and daily temperature dataset for the study area based on meteorological data, and use the Rclimdex toolkit in R language to calculate four extreme precipitation elements: R20mm, Rx5day, CWD, and SDII. R20mm refers to the total number of days with daily precipitation ≥20mm per year; Rx5day refers to the maximum 5-day precipitation; CWD refers to the maximum consecutive number of days with daily precipitation ≥1mm; and SDII refers to the ordinary daily precipitation intensity, which is the ratio of the total amount of daily precipitation ≥1mm to the total number of days.

[0048] For surface runoff data in the inundation state index layer, the SWAT (Soil and Water Assessment Tool) model is used for simulation at the watershed and city scales, inputting hydrological and meteorological data, land cover data, soil data, and topographic data for calculation; the SWMM (Storm Water Management Model) model is used for simulation at the drainage zoning scale. The SWAT model is suitable for large-scale studies, while the SWMM model is suitable for small-scale studies; therefore, the SWAT model is used at the watershed and city scales, and the SWMM model is used at the drainage zoning scale. The SWAT model calculates using hydrological and meteorological data, land cover data, soil data, and topographic data as inputs, and outputs a raster map of the spatial distribution of surface runoff. The SWMM model requires hydrological and meteorological data, drainage network data, soil data, land use data, and topographic data as inputs, and outputs a raster map of the surface runoff of the study area.

[0049] Regarding the calculation of surface inundation range elements in the inundation state index layer, the CN (Curve Number) value is first calculated using the SWAT model. Then, the SCS-CN (Soil Conservation Service–Curve Number) model is modified based on the underlying surface conditions of the study area to calculate the water production volume. Finally, the inundation range is calculated using ArcGIS software.

[0050] Specifically, firstly, based on the rainfall patterns and planned flood control standards of the study area, the return period rainfall is calculated. Secondly, the SWAT model can be used to calculate... Value and catchment area The total runoff can be calculated using the following formula (1). The initial loss value of 0.05 should be determined based on the specific conditions of the study area. (1) in, Total runoff; Rainfall; For soil saturation water storage, ; The value is a dimensionless parameter that reflects the hydrological runoff characteristics of the watershed before rainfall and is calculated by the SWAT model.

[0051] Further based on the catchment area Using the formula Calculate the ideal state volume of the depression in the flooded area Since the ideal volume approaches the passive inundation volume of the catchment area under rainfall conditions infinitely, the ArcGIS reclassification tool is used to calculate and verify the runoff depth value based on the volume, extract the inundation height range of each catchment area and mosaic it to obtain an inundation distribution raster map with the corresponding return period.

[0052] In the rainwater erosion index layer, the Topographic Wetness Index (TWI) predicts the surface moisture accumulation potential by quantifying the interaction between slope and catchment area. The calculation formula is as follows: (2) In the rainwater erosion index layer, the sediment transport index (STI) is a comprehensive indicator that quantifies the ability of water flow to carry sediment. The calculation formula is as follows: (3) in, The uphill runoff area is the area of ​​runoff per unit contour line length. The slope. and These are the calculated values ​​for the topographic humidity index and the sediment transport index, respectively.

[0053] Climate regulation and water conservation elements in the ecosystem service function indicator layer can be calculated using InVEST software, specifically the carbon storage module and the water production module.

[0054] Specifically, climate regulation indicators quantify the carbon storage capacity of ecosystems, reflecting the contribution of the ecological environment to greenhouse gas emission reduction, thereby mitigating the risk of extreme precipitation. The carbon storage capacity of ecosystems can be calculated using the carbon storage module in the InVEST software. The data required for the carbon storage module calculation includes land use data and carbon density data for various land use types (including aboveground biomass carbon density, belowground biomass carbon density, soil carbon density, and litter organic matter carbon density, with values ​​obtained from literature reviews).

[0055] Water conservation indicators characterize the ecosystem's ability to intercept rainwater and regulate runoff. First, the water yield is calculated using the water production module in the InVEST software, and then corrected for soil permeability and topographic factors to obtain the water conservation capacity. The InVEST model requires input data including precipitation, evaporation, root depth, available water content in plants, land use, biophysical tables, Z-parameters, and watershed boundary data. Regional precipitation and evaporation data can be obtained from the National Geoscience Data Center website. Root depth data can be obtained from the REF_DEPTH data in the World Soil Database (HWSD). Available water content in plants can be calculated based on indicators in the World Soil Database (HWSD), using the following formula: (4) in, PAWC The effective water content of plants, sand %, silt %, clay The percentages represent the proportions of sand, gravel, silt, and clay particles in the soil. OM This indicates the organic matter content in the soil. Land use data can be obtained from the National Earth System Science Data Sharing Service Platform.

[0056] The required fields in the biophysical table include land use code (LUCODE), root depth (root_depth), vegetation cover data (lulc_veg), and reference evapotranspiration (kc). Vegetation cover data is assigned a value based on land use type: 1 for vegetable areas such as woodland, shrubland, grassland, and cultivated land, and 0 for non-vegetable areas such as bare land, impermeable surfaces, and water bodies. Root depth and reference evapotranspiration are empirical values ​​obtained from literature reviews in the studied area. The Z parameter is inversely proportional to water yield, with a default value of 1.5, which needs to be adjusted based on calculation results after multiple trials.

[0057] The InVEST model calculates the water yield for the study area. Water conservation capacity is further estimated based on the water yield, taking into account factors such as soil depth, permeability, and topography. The calculation formula is as follows: (5) Where WR is the annual average water conservation capacity (mm), V TI is the velocity coefficient, and TI is the topographic index. K soil Where is the soil saturated hydraulic conductivity (cm / d), and WY is the water yield. Flow velocity coefficient. V The information can be obtained from the reference "Fu Bin, Xu Pei, Wang Yukuan, et al. Spatial pattern of water conservation function in Dujiangyan City [J]. Acta Ecologica Sinica, 2013, 33(03):789-797." The formula for calculating the topographic index is as follows: (6) in, The area of ​​the uphill catchment area is given per unit contour line length. β The slope of a local area can be calculated in ArcGIS.

[0058] K soil The data calculation formula is as follows: (7) in, Soil sand content (%); The soil clay content is expressed as a percentage (%).

[0059] Step 3: Based on the correlation between elements, select the final multi-scale, full-cycle stormwater resilience element library.

[0060] Specifically, based on the characteristics and data conditions of various elements in the multi-scale, full-cycle stormwater resilience element database, the research units can be divided into three geospatial levels: watershed, city, and drainage zone. The element characteristics at different scales are reflected in Table 1, which describes the construction of the element database. The corresponding element data is obtained using step 2, and studies are conducted at each of the three scales. Using ArcGIS hydrological analysis tools and the SWAT model, the main river system and urban administrative divisions of the watershed can be identified. The watershed scale is determined based on the regional planning, and the city scale is determined based on the boundaries of the urban administrative regions. Furthermore, based on water network data and major water conservancy projects within the watershed, river catchment points and catchment areas are calculated, and watershed hydrological response units are sequentially divided. These units are then modified based on the layout of the drainage network, serving as the research unit scope for the drainage zone.

[0061] Among these, the watershed scale represents the broadest research area; therefore, a specific watershed should be identified as the research object first. In China, this includes seven first-order watersheds: the Yangtze River, Yellow River, Pearl River, Huai River, Hai River, Liao River, and Songhua River. Urban-scale division is based on the boundaries of urban administrative regions. Drainage zoning requires the combined use of ArcGIS and SWAT models. First, the SWAT model is used to calculate the river catchment points and catchment areas of the studied watershed (region), and then further subdivided into sub-watersheds. Required data includes ground elevation data and river system data. Ground elevation data comes from a joint measurement by NASA and the National Institute of Mapping and Geomatics (NIMA), while river system data can be obtained from the OpenStreetMap website. Based on the sub-watershed division, combined with land use data, meteorological data, and soil data, the SWAT model is used to further subdivide into hydrological response units. The layout of the integrated drainage network is used to refine the hydrological response units. The boundaries of the hydrological response units are fine-tuned based on the integrity of the main drainage network and drainage network zoning, thereby determining the scope of the research unit, which serves as the drainage zoning scale.

[0062] After dividing the study area into three scales—watershed, urban, and drainage zone—the three scales are calculated independently in the subsequent assessment of stormwater resilience using the entropy weight method-VIKOR approach. However, the correlation between indicators (elements) affects the accuracy of the entropy weight method calculation results; therefore, a correlation analysis of the indicator data in the element database is necessary before applying the entropy weight method. Spearman correlation analysis can be performed using SPSS software. Correlation analysis is conducted on the element data at the three scales in Table 1. Based on the calculation results, indicators with high correlation are removed, and the final indicator system is obtained according to the specific circumstances of the study area.

[0063] Specifically, Spearman correlation analysis is used to measure the correlation between the elements (indicators) contained in each spatial scale in the multi-scale full-cycle stormwater resilience element database. The indexes in the element database are further screened to remove the highly correlated indicators, thereby selecting the final multi-scale full-cycle stormwater resilience element database for the corresponding spatial scale.

[0064] Step 4: Use the entropy weight method to calculate the weight of each element in the final multi-scale full-cycle stormwater resilience element database.

[0065] The entropy weight method was used to calculate the element weights at three scales: watershed, city, and drainage zone. The weights of the five systems (driving forces, pressures, states, impacts, and responses) within the DPSIR framework at each scale were calculated, along with the weights of individual elements. Step 4 used the final element library filtered in Step 3. The weights of the five systems (driving forces, pressures, states, impacts, and responses) within the DSPIR framework at each scale can be obtained by adding the weight values ​​of the element-level indicators they contain. This allows for the macroscopic identification of the system with the greatest impact on stormwater resilience among the five systems. The calculation method for individual element weights specifically includes steps 4.1 to 4.3, calculated separately for each spatial scale of the study area.

[0066] Step 4.1: For each spatial scale of the study area, based on the index attributes of each element in its final multi-scale full-cycle rainwater resilience element database, standardize the data of each element to obtain the index value of each element after standardization.

[0067] First, each element is standardized. Since there are positive and negative indicators, they are standardized according to formulas (8) and (9) respectively: (8) (9) In the formula, It is the first in the final multi-scale, full-cycle stormwater resilience element database at a certain spatial scale. The indicators (elements) in the first The original values ​​(raw data) in each cell. yes The index values ​​after standardization. and These are the first and second units of the study area at this spatial scale. The maximum and minimum values ​​of each indicator.

[0068] Step 4.2: Calculate the information entropy of each element based on the standardized index values ​​of each element's data.

[0069] The entropy weight method is used to determine the weights of each indicator system. First, the weights of each indicator are calculated. Information entropy : (10) in, (11) The data obtained for each indicator (feature) in the feature layer is raster data. This represents the number of pixels in the raster data.

[0070] Step 4.3: Calculate the weight of each element based on its information entropy, using the following formula: (12) In the formula, It is the first The entropy of each indicator (element), It is the first The weight of each indicator (factor).

[0071] The above method is used to calculate the weight value of each indicator (element) in the final multi-scale full-cycle stormwater resilience element database for each scale. This prepares for calculating the group effect value and individual regret value in step 5.

[0072] Step 5: Based on the weight calculation, the VIKOR multi-criteria decision method is used to calculate the stormwater resilience at each spatial scale, and the geographic detector is used to analyze the most significant factors from two aspects: spatial scale and stormwater flooding stage.

[0073] Building upon step 4, the VIKOR multi-criteria decision-making method was used to assess stormwater resilience at three different scales. The benefit ratio was calculated by integrating group utility and individual regret values. This allows for the acquisition of multi-scale, full-cycle rainfall resilience. Based on the rainfall resilience calculation results, a spatiotemporal distribution pattern of rainfall resilience is constructed, providing scientific guidance for optimizing and improving multi-scale rainfall resilience. Furthermore, by identifying the most significant factors affecting each stage of rainfall resilience, targeted optimization strategies for rainfall resilience can be proposed.

[0074] Step 5 specifically includes steps 5.1 to 5.5.

[0075] Step 5.1: For each spatial scale of the study area, determine the positive ideal solution and the negative ideal solution based on the standardized index values ​​of each element in the final multi-scale full-cycle rainwater resilience element database.

[0076] The positive ideal solution is the maximum value of each indicator, and the negative ideal solution is the minimum value of each indicator.

[0077] The ideal solution is expressed as follows: (13) in, yes The index values ​​after standardization. Indicates the first Each indicator is in the range of 1 to The maximum value among the pixels is . . From 1 to The maximum value of each indicator among the indicators. That is, the set of maximum values ​​for each indicator. , This refers to the number of indicators in the final multi-scale, full-cycle rainstorm resilience element database at a certain spatial scale. , For the first The number of pixels in the raster data for each indicator.

[0078] The negative ideal solution is: (14) The same applies to negative ideal solutions. Indicates the first Each indicator is in the range of 1 to The minimum value among all pixels is taken as the minimum value. . From 1 to The minimum value of each of the indicators. That is, the set of minimum values ​​for each indicator.

[0079] Step 5.2: Calculate the group effect value and individual regret value based on the positive ideal solution and the negative ideal solution.

[0080] No. Group effect value of each indicator and individual regret value The calculation formula is as follows: (15) (16) in, It is the first The weight of each indicator (factor). Indicates the first The positive ideal solution for each indicator Indicates the first The negative ideal solution of each indicator. Indicates to The maximum value is taken for some calculation results.

[0081] Step 5.3: Calculate the benefit ratio based on the group effect value and the individual regret value.

[0082] Profit Ratio The calculation formula is as follows: (17) in, The decision coefficient represents the degree to which the evaluation is biased towards group effects or individual regrets. The larger the value, the more it leans towards the group effect value. ; The smaller the value, the more it leans towards the individual regret value. . This is the maximum value among the group effect values. This is the minimum value among the group effect values. and These represent the maximum and minimum values ​​of the individual regret value, respectively.

[0083] Step 5.4: Calculate stormwater resilience based on the benefit ratio.

[0084] Rainwater resilience The calculation formula is as follows: (18) Rainfall resilience index The value ranges from 0 to 1. The higher the value, the stronger the resilience of the region to rainstorms and floods, and vice versa.

[0085] Based on a three-scale division of watershed, city, and drainage zone, this application calculates stormwater resilience using the final multi-scale, full-cycle stormwater resilience element database for each scale, thus forming a spatiotemporal distribution pattern of stormwater resilience. The study area is divided into three scales: watershed, city, and drainage zone. Stormwater resilience is calculated at each scale using the method described in step 5, with the difference being that the element database differs for each scale. The final calculation results are presented as raster data, forming stormwater resilience raster maps at the watershed, city, and drainage zone scales. These stormwater resilience raster maps can display areas with high and low stormwater resilience at different scales. In practical engineering, areas with low resilience should be prioritized for improvement to reduce losses caused by rainstorm floods.

[0086] Step 5.5: Use a geographic detector to analyze the most significant factors from two aspects: spatial scale and the stage of rainstorm and flooding.

[0087] Based on the acquisition of stormwater resilience at the watershed-city-drainage zone scale, a geospatial detector is used to analyze the interaction between stormwater resilience and indicators (factors), exploring how factors such as land use, population density, and rainwater gradient affect the spatial distribution and intensity of stormwater resilience. Based on the four stages of stormwater flooding, the significance of indicator effects can be obtained from the geospatial detector results, identifying the most significant factors affecting different stages of stormwater flooding. Through a multi-scale, full-cycle assessment of stormwater resilience, targeted optimization strategies for stormwater resilience are proposed.

[0088] Specifically, for each spatial scale of the study area, elements from the final multi-scale, full-cycle stormwater resilience element database are used as independent variables, and the corresponding stormwater resilience is used as the dependent variable. These elements are then input into the geographic detector model to obtain the significance of each element. Based on the division of the action stages of each element (indicator) in Table 1, the factors with the most significant impact at each stage can be identified. This allows for targeted mitigation measures to be taken at different stages of rainstorm and flood disasters to resist the damage of rainstorm and flood disasters to the urban environment.

[0089] Based on the above assessment of rainwater resilience at three scales, a resilience distribution map in geospatial space can be identified. Combined with the most significant factors in the rainstorm and flood cycle, targeted improvement strategies can be proposed for low-resilience areas in four stages: the initial stage of rainstorm, the formation stage of flood disaster, the duration stage of flood disaster, and the recovery stage of flood disaster.

[0090] The multi-scale, full-cycle stormwater resilience assessment method proposed in this application first standardizes the element data after screening, then calculates the weight of each element using the entropy weight method, and finally calculates stormwater resilience based on the VIKOR multi-criteria decision-making method. By inputting the indicators (elements) as independent variables and stormwater resilience as the dependent variable into the geographic detector model, the significance of each indicator can be obtained. Based on the action stages of each indicator in Table 1, the factors with the most significant impact in each of the four stages can be identified. According to the spatial distribution pattern of stormwater resilience at the three scales of watershed, city, and drainage zone, spatial characteristics are summarized for high-resilience areas, providing successful experience for the generation of resilience strategies; for low-resilience areas, key improvements and optimizations are needed, and a full-cycle stormwater resilience enhancement strategy can be formed based on the four stages of stormwater and flood action.

[0091] This application constructs a comprehensive rainwater resilience database based on four stages of rainstorm and flood impact: the initial stage of heavy rainfall, the formation stage of flood disaster, the duration stage of flood disaster, and the recovery stage of flood disaster, as well as three scales: watershed, city, and drainage zone. This overcomes the limitations of existing research that focuses on a single scale and, considering the complex changes in current extreme climate and the characteristics of rainstorm and flood disasters, establishes a multi-scale, full-cycle rainwater resilience database. This application effectively supplements the research results on rainwater resilience at multiple scales and promotes in-depth research on urban resilience, providing scientific guidance for optimizing and improving rainwater resilience. By establishing a watershed-city-drainage zone rainwater resilience assessment system to conduct multi-scale, full-cycle resilience evaluation, it is possible to visualize the level of resilience function, identify potential risks and weaknesses in rainwater resilience, and thus take targeted and effective measures to alleviate rainstorm and flood problems, improving the flood control capacity and resilience of watersheds and cities.

[0092] In one exemplary embodiment, this application also provides a computer device, which may be a server or a terminal. The computer device includes a processor, a memory, an input / output interface, and a communication interface. The processor, memory, and input / output interface are connected via a system bus, and the communication interface is connected to the system bus via the input / output interface. The processor of the computer device provides computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores an operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage medium. The input / output interface of the computer device is used for exchanging information between the processor and external devices. The communication interface of the computer device is used for communication with external terminals via a network connection. When the computer program is executed by the processor, it implements the aforementioned multi-scale, full-cycle rainfall resilience assessment method.

[0093] In one exemplary embodiment, this application also provides a computer-readable storage medium having a computer program stored thereon that, when executed by a processor, implements the multi-scale, full-cycle stormwater resilience assessment method.

[0094] In one exemplary embodiment, this application also provides a computer program product, including a computer program that, when executed by a processor, implements the multi-scale, full-cycle stormwater resilience assessment method.

[0095] It will be understood by those skilled in the art that all or part of the processes in the methods of the above embodiments can be implemented by hardware related to computer program instructions. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any reference to memory or other media in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory may include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory may include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM).

[0096] It should be noted that the information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of the relevant data must comply with relevant regulations.

[0097] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0098] This document uses specific examples to illustrate the principles and implementation methods of this application. The descriptions of the above embodiments are only for the purpose of helping to understand the methods and core ideas of this application. Furthermore, those skilled in the art will recognize that, based on the ideas of this application, there will be changes in the specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. A multi-scale, full-cycle stormwater resilience assessment method, characterized in that, include: Based on the cycle of rainstorm and flood and the three spatial scales of watershed, city and drainage zone, a multi-scale full-cycle rainstorm resilience element database is constructed. The multi-scale full-cycle rainstorm resilience element database includes a target layer, an indicator layer and an element layer, as well as the corresponding action stage and indicator attributes of each element. The action stages of each element include the rainstorm initiation stage, the flood disaster formation stage, the flood disaster duration stage and the flood disaster recovery stage. Collect and calculate the data of each element in the element layer during the entire cycle of responding to rainstorms and floods at three spatial scales: watershed, city, and drainage zone. The final multi-scale, full-cycle stormwater resilience element database was selected based on the correlation between elements. The weight of each element in the final multi-scale, full-cycle stormwater resilience element database is calculated using the entropy weight method. Based on the weight calculation, the VIKOR multi-criteria decision method is used to calculate the stormwater resilience at each spatial scale, and the geographic detector is used to analyze the most significant factors from two aspects: spatial scale and stormwater flooding stage. The aforementioned multi-scale, full-cycle stormwater resilience database is constructed based on the stormwater and flood cycle and three spatial scales: watershed, city, and drainage zone. Specifically, it includes: The entire cycle of rainstorm and flood effects is divided into four stages: the rainstorm initiation stage, the flood formation stage, the flood duration stage, and the flood recovery stage. The study area was divided into three spatial scales: watershed, urban area, and drainage zone. A multi-scale, full-cycle stormwater resilience element database is constructed based on the DPSIR framework. The database is divided into three spatial scales: watershed, city, and drainage zone. The target layer of each spatial scale includes five systems: driving force, pressure, state, impact, and response. The driving forces at the watershed scale include two indicator layers: urban expansion and extreme precipitation. Urban expansion corresponds to factors such as land use, population density, the proportion of the aging population, and GDP per capita. Extreme precipitation corresponds to factors such as R20mm, Rx5day, CWD, and SDII. The pressures at the watershed scale include three indicator layers: natural environment, hydrological data, and infrastructure. Natural environment factors include ground elevation, rainwater gradient, ground roughness, and soil permeability. Hydrological data factors include river network density and water connectivity. Infrastructure factors include emergency shelter density, regional road density, regional medical facility density, and regional fire station density. The watershed-scale status includes two aspects: inundation status and water storage capacity. At the indicator level, the elements corresponding to the inundation state include surface runoff and surface inundation area; the elements corresponding to the regulation capacity include green space ratio, reservoir regulation capacity, river regulation capacity, and flood storage area capacity. At the watershed scale, the impacts include three indicator levels: economic impact, rainwater erosion, and affected population. The economic impact corresponds to economic losses; the rainwater erosion corresponds to topographic humidity index and sediment transport index; and the affected population corresponds to the percentage of vulnerable population. At the watershed scale, the response includes three indicator levels: ecosystem service function, financial support, and rainwater monitoring. The ecosystem service function corresponds to climate regulation and water conservation; the financial support corresponds to investment in flood control; and the rainwater monitoring corresponds to a rainwater monitoring system. The driving forces at the urban scale include two indicator layers: urban expansion and extreme precipitation. Urban expansion corresponds to factors such as land use, population density, the proportion of the aging population, and GDP per capita. Extreme precipitation corresponds to factors such as R20mm, Rx5day, CWD, and SDII. The pressures at the urban scale include five indicator layers: natural environment, hydrological data, infrastructure, water conservancy facilities, and urban construction. Natural environment factors include ground elevation, rainwater slope, ground roughness, and soil permeability. Hydrological data factors include water system area and water connectivity. Infrastructure factors include emergency shelter density, regional road density, regional medical facility density, and regional fire station density. Water conservancy facilities factors include dam flood control standards, drainage network density, drainage network diameter, and rainwater storage facility density. Urban construction factors include road width and building density. The city-scale status includes two indicator layers: inundation status and water storage capacity. The inundation status corresponds to the elements of surface runoff and surface inundation range, while the water storage capacity corresponds to the elements of green space ratio, reservoir storage capacity, river storage capacity, and flood detention area capacity. The city-scale impact includes three indicator layers: economic impact, rainwater erosion, and affected population. The economic impact corresponds to the element of economic loss, the rainwater erosion corresponds to the elements of topographic humidity index and sediment transport index, and the affected population corresponds to the element of the percentage of vulnerable population. The city-scale response includes four indicator layers: ecosystem service function, financial support, rainwater monitoring, and blue-green water storage measures. The ecosystem service function corresponds to the elements of climate regulation and water conservation, the financial support corresponds to the element of flood control investment, the rainwater monitoring corresponds to the element of rainwater monitoring system, and the blue-green water storage measures correspond to the element of sponge city facilities. The driving forces at the drainage zoning scale include two indicator layers: urban expansion and extreme precipitation. Urban expansion corresponds to factors such as land use, population density, proportion of aging population, and GDP per capita. Extreme precipitation corresponds to factors such as R20mm, Rx5day, CWD, and SDII. The pressures at the drainage zoning scale include four indicator layers: natural environment, hydrological data, water infrastructure, and urban construction. Natural environment factors include ground elevation, rainwater slope, ground roughness, and soil permeability. Hydrological data corresponds to the area of ​​waterways. Water infrastructure factors include drainage network density, drainage network diameter, and rainwater storage facility density. Urban construction factors include… The elements at the drainage zoning scale include road width and building density; the state at the drainage zoning scale includes two indicator layers: flooding state and storage capacity. The elements corresponding to flooding state include surface runoff and surface flooding range, while the elements corresponding to storage capacity include green space ratio and road connectivity; the impacts at the drainage zoning scale include two indicator layers: rainwater erosion and affected population. The elements corresponding to rainwater erosion include topographic humidity index and sediment transport index, while the elements corresponding to affected population are the percentage of vulnerable population; the response at the drainage zoning scale includes two indicator layers: rainwater monitoring and blue-green storage measures. The element corresponding to rainwater monitoring is the rainwater monitoring system, and the element corresponding to blue-green storage measures is sponge city facilities. Each element corresponds to one or more of the following four stages: the beginning of the rainstorm, the formation of the flood disaster, the duration of the flood disaster, and the recovery stage of the flood disaster; the indicator attribute corresponding to each element is positive or negative.

2. The multi-scale, full-cycle stormwater resilience assessment method according to claim 1, characterized in that, The study area is divided into three spatial scales: watershed, urban, and drainage zone. Specifically, this includes: The watershed scale to which it belongs is determined based on the regional planning of the study area; Determine the city scale based on the boundaries of the city's administrative regions; Using ArcGIS hydrological analysis tools and the SWAT model, river catchment points and catchment areas are calculated, and watershed hydrological response units are divided accordingly. The hydrological response units are then modified based on the layout of the drainage network to form a research unit range that conforms to the hydrological process and engineering reality as the drainage zoning scale.

3. The multi-scale, full-cycle stormwater resilience assessment method according to claim 2, characterized in that, The final multi-scale, full-cycle stormwater resilience element database, selected based on the correlation between elements, specifically includes: Spearman correlation analysis was used to measure the correlation between elements at each spatial scale in the multi-scale full-cycle stormwater resilience element database. Elements with high correlation were removed, thereby selecting the final multi-scale full-cycle stormwater resilience element database for the corresponding spatial scale.

4. The multi-scale, full-cycle stormwater resilience assessment method according to claim 3, characterized in that, The calculation of the weight of each element in the final multi-scale, full-cycle stormwater resilience element database using the entropy weight method specifically includes: For each spatial scale of the study area, the data of each element are standardized according to the index attributes of each element in the final multi-scale full-cycle rainwater resilience element database, so as to obtain the index value of each element after standardization. Calculate the information entropy of each element based on the standardized index values ​​of each element's data; The weight of each element is calculated based on its information entropy.

5. The multi-scale, full-cycle stormwater resilience assessment method according to claim 4, characterized in that, Based on the weighted calculation, the VIKOR multi-criteria decision method is used to calculate the stormwater resilience at each spatial scale, specifically including: For each spatial scale of the study area, the positive ideal solution and the negative ideal solution are determined based on the standardized index values ​​of each element in the final multi-scale full-cycle rainwater resilience element database. Calculate the group effect value and individual regret value based on the positive and negative ideal solutions; Calculate the benefit ratio based on the group effect value and the individual regret value; Rainwater resilience is calculated based on the benefit ratio.

6. The multi-scale, full-cycle stormwater resilience assessment method according to claim 5, characterized in that, The analysis of the most significant influencing factors using geographic detectors examines both the spatial scale and the stages of rainstorm and flooding events. Specifically, this includes: For each spatial scale of the study area, the elements in the final multi-scale full-cycle rainwater resilience element database are used as independent variables, and the corresponding rainwater resilience is used as the dependent variable. The data are input into the geographic detector model to obtain the significance of each element. Based on the action stage of each element and its significance, the elements with the most significant impact in the four action stages are identified.

7. A computer device, comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that the processor executes the computer program to implement the multi-scale, full-cycle stormwater resilience assessment method according to any one of claims 1 to 6.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that, When executed by a processor, the computer program implements the multi-scale, full-cycle stormwater resilience assessment method as described in any one of claims 1 to 6.

9. A computer program product, comprising a computer program, characterized in that, When executed by a processor, the computer program implements the multi-scale, full-cycle stormwater resilience assessment method as described in any one of claims 1 to 6.

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