Flood risk measurement method considering mountain city surrounding terrain catchment effect

Abstract

The invention discloses a flood risk measurement method considering a mountain city surrounding terrain catchment effect, and the method comprises the steps: building a buffer region through a spatial analysis method based on high-resolution remote sensing image data, and precisely defining an urban catchment boundary; a digital elevation model (DEM) and a hydrological analysis tool are utilized to extract a runoff network of mountainous regions around a city and vectorize river network data so as to improve the precision of watershed hydrological information; in combination with urban boundary and river network information, through topographic analysis and hydrological modeling technologies, identifying potential dump points of mountain torrents, and determining a water flow dump path; dividing a research area into a plurality of space grid units, calculating the shortest distance from each grid to a dumping point by adopting a space distance measuring and calculating method, and giving a risk level to the dumping point based on terrain and catchment conditions; and comprehensively considering disaster-inducing factors and disaster-bearing capacities in each grid unit, calculating disaster-inducing indexes and disaster-bearing indexes of mountain torrent disasters, and further constructing a systematic urban mountain torrent risk assessment framework. The method focuses on the risk measurement of the sudden flood in the mountainous area with the complex terrain, and combines various technical means including remote sensing, GIS, urban planning and the like. The comprehensive and accurate urban mountain torrent risk measurement method is provided by comprehensively evaluating the hydrological characteristics of the area around the city and the building layout in the city. Therefore, city planning and management departments can better formulate flood control measures, and the anti-disaster capability of the city in mountain torrent events is improved.

Description

Technical Field

[0001] The present invention relates to the field of urban disasters, and in particular to a flood risk measurement method that takes into account the water collection effect of the terrain surrounding a mountain city. Background Art

[0002] With the intensification of global warming and the advancement of urbanization on sloping land, inland mountainous cities are facing an increasingly severe threat from flash floods on surrounding slopes. Urbanization has led to significant changes in land use patterns, which in turn reduces soil moisture retention and prolongs rainwater retention. Furthermore, infrastructure in mountainous cities is generally inadequate, including a lack of drainage systems and inadequate river management, which reduces stormwater drainage capacity and increases the probability of flash floods. These factors combine to rapidly transform rainwater into torrents during extreme climate events (such as heavy rain), significantly increasing the risk of flash floods. Therefore, accurately measuring the flash flood risk in urban areas adjacent to sloping land has become a critical task for developing effective flood prevention measures and improving urban disaster resilience.

[0003] Traditional flash flood risk assessment methods often fail to fully consider the impact of hillside water collection and urbanization on the regional hydrological environment. They also fail to clearly delineate between urban areas and confluent slopes to analyze the threat posed by runoff from surrounding slopes to urban areas, resulting in one-sided and inaccurate assessment results. Furthermore, the relevant assessment indicators used for plain cities fail to fully reflect the complex risk characteristics of mountainous cities. Therefore, there is an urgent need to develop a multidimensional approach that integrates factors such as water collection characteristics, topography, and urban planning to achieve a more comprehensive and accurate urban flash flood risk assessment. This method combines relevant technologies and methods from hydrology and surveying to identify the sources of flash flood risk in urban areas, delineate the boundaries between urban areas and slopes, and extract information about river networks surrounding urban areas to accurately assess the hydrological characteristics of the catchment area. Specifically, by dividing the urban center into grid cells and comprehensively considering multiple factors such as the hazard index, point of interest (POI) distribution within each cell, building density, and road density, a more detailed risk assessment is achieved. The innovation of this method lies in its integration of multiple technical approaches, which improves the accuracy and comprehensiveness of the assessment, providing a scientific basis for urban planning and management departments to more effectively formulate flood prevention strategies and enhance urban disaster preparedness. Summary of the Invention

[0004] To address the flash flooding challenges faced by mountainous cities, this paper aims to provide a flood risk assessment method that takes into account the water collection effects of the surrounding terrain. This method fully considers the surrounding topography, runoff collection, and urban development of mountainous cities. The specific implementation process is as follows:

[0005] A flood risk measurement method that takes into account the water collection effect of the terrain around mountain cities includes five parts: rainfall catchment boundary delineation, runoff simulation, river network extraction and vectorization, flash flood dumping point extraction, dumping point distance and dumping point grade calculation, and construction of an urban flash flood risk measurement system.

[0006] Step 1: Based on high-resolution remote sensing imagery data, spatial analysis methods are used to construct buffer zones and accurately define urban catchment boundaries. The steps for this part are as follows:

[0007] S1: Extract the city center using high-definition satellite images or city reference data;

[0008] S2: Considering the local precipitation and hilly conditions, the buffer zone is extended outward. This area is considered to be the effective area for surrounding slopes to protect the city center from flooding.

[0009] Step 2: Using a digital elevation model (DEM) and hydrological analysis tools, we extracted the runoff network in the mountainous areas surrounding the city and vectorized the river network data to improve the accuracy of the watershed hydrological information. The steps for this part are as follows:

[0010] S1: Fill depressions and remove protrusions based on digital terrain model (DEM) data;

[0011] S2: D8 algorithm is used to simulate surface runoff;

[0012] S3: Extract and vectorize key river network information such as runoff direction, cumulative runoff, and river network classification;

[0013] Step 3: Combined with city boundaries and river network information, terrain analysis and hydrological modeling techniques are used to identify potential flash flood discharge points and determine the flow discharge path. The steps for this part are as follows:

[0014] S1: Check, revise and eliminate runoff;

[0015] S2: Intersect the runoff vector with the city center boundary to obtain the pour point

[0016] Step 4: Divide the study area into several spatial grid cells. Use the spatial distance measurement method to calculate the shortest distance from each grid cell to the pour point. Then assign a risk level to the pour point based on the terrain and catchment conditions. The steps for this part are as follows:

[0017] S1: Select an appropriate grid size as the basic measurement unit and calculate the distance from the grid to the pouring point;

[0018] S2: Classify the dumping points according to river flow and grade;

[0019] Step 5: Comprehensively consider the disaster-causing factors and disaster-bearing capacity of each grid cell, calculate the flash flood disaster hazard index and disaster-bearing index, and then build a systematic urban flash flood risk assessment framework. The steps of this part are as follows:

[0020] S1: Calculate the distance to the dumping point and the dumping point grade as the disaster index of a grid unit;

[0021] S2: Calculate the road network density, POI density, and building density of the grid unit and combine them as the disaster resistance index of a certain grid unit.

[0022] S3: Calculate the disaster hazard index and bearing index of a grid unit and combine them as the flash flood risk index within the grid unit. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are merely schematic diagrams of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying any creative work.

[0024] Figure 1 It is a schematic diagram of the overall structure of the present invention;

[0025] Figure 2 This is the result map of surface runoff extraction and pouring point identification around the main urban area in the present invention;

[0026] Figure 3 This is the disaster index distribution map of the main urban area in the present invention;

[0027] Figure 4 The present invention provides a distribution map of grid unit buildings, road networks, POI density and disaster resistance index in the main urban area;

[0028] Figure 5 This is the comprehensive risk map of flash floods in the main urban area of ​​the present invention; DETAILED DESCRIPTION

[0029] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0030] Specifically, in this case study, Lanzhou City was selected as the case study area. Although located in an arid region, the rapid urbanization of slopes in recent years has led to an increase in impervious surfaces on slopes, reduced rainwater infiltration, and increased urban flooding risk.

[0031] The following is a section based on high-resolution remote sensing image data and spatial analysis methods to construct a buffer zone and accurately define the urban rainfall catchment boundary:

[0032] Step 1: Delineate runoff analysis boundaries using high-definition satellite imagery and vectorization of urban flood-prone areas.

[0033] Step 2: Considering that Lanzhou is surrounded by mountains, has loess soil and a small slope, and has a large amount of runoff infiltration, based on field investigations and expert experience, a 10km buffer zone is created outward from the central urban area as a runoff extraction area.

[0034] The following is a section on using a digital elevation model (DEM) and hydrological analysis tools to extract the runoff network in the mountainous area surrounding the city and vectorize the river network data to enhance the accuracy of the watershed hydrological information:

[0035] Step 1: DEM data is preferably measured data with smaller errors. Since this data is difficult to obtain, the easily available SRTM 30DEM is selected. First, the existing DEM data is filled. Due to common errors caused by data resolution or rounding elevations to the nearest integer value, depressions should be filled to ensure that basins and rivers are correctly demarcated. If depressions are not filled, the generated water network may appear discontinuous.

[0036] Step 2: Analyze the runoff direction (Flow Direction) of the filled DEM. The most common hydrological analysis algorithm used in this case is the D8 algorithm. Based on the flow direction data, the accumulation raster data is obtained to obtain the runoff flow (Flow Accumulation). In particular, considering that the Yellow River runs through the central urban area, the runoff flow threshold is set to the average flow of the Yellow River of 1000m. 3 / h or above, thus retaining runoff that threatens urban areas.

[0037] Step 3: Classify the extracted river network raster and perform vector extraction on it.

[0038] The following is a combination of urban boundary and river network information, terrain analysis and hydrological modeling technology to identify potential flash flood discharge points and determine the possible water discharge paths:

[0039] Step 1: Based on the river network extraction results in the previous step and the boundary of the central urban area, eliminate the invalid runoff that poses no threat to the main urban area and screen the runoff that intersects with the boundary.

[0040] Step 2: Multiple runoffs with a distance difference of less than 500m are regarded as the main runoff of the river network, and the runoff grades are superimposed.

[0041] Step 3: The intersection of a single runoff and the central urban area boundary is selected as the discharge point of the mountain torrent to the central urban area, and the midpoint of the intersection of the fused runoff and the urban area boundary is selected as the discharge point of the mountain torrent.

[0042] The following is a section that divides the study area into several spatial grid cells, applies the spatial distance measurement method, calculates the shortest distance from each grid cell to the pour point, and assigns different pour point risk levels based on the terrain and catchment conditions:

[0043] Step 1: Use GIS technology to divide the central urban area into several 500*500m grid cells, and use the grid center as the center of the area. Use the Euclidean distance calculation method to calculate the distance from each pouring point to the center point of each grid cell.

[0044] The following is a section on calculating the flash flood hazard index and disaster tolerance index by comprehensively considering the hazard factors and disaster tolerance capacity of each grid unit, and then constructing a systematic urban flash flood risk measurement framework:

[0045] Step 1: The flash flood risk (GFR) within the grid area includes the disaster index (DI) and the disaster index (TI). The DI disaster index includes the distance from the grid center to the pouring point (L) and the pouring point grade (M);

[0046] The calculation method of the disaster index is as follows:

[0047]

[0048] Where, DI i represents the disaster index of the i-th grid cell, S n Represents the dumping level of the nth dumping point, L i represents the distance from the i-th grid cell to the n-th dumping point;

[0049] Step 2: Disaster Susceptibility Index (TI) includes building density (GBD), point of interest density (GPD), and road network density (GRD). The weights of the indicators are assigned according to the three factors. The calculation method of the disaster susceptibility index is as follows:

[0050] TI i =(GPD i ×0.4+GBD i ×0.2+GRDi ×0.4)

[0051] Where TI i Represents the disaster index of the i-th grid unit, GPD i Represents the POI density of the i-th grid cell, GBD i Represents the building density of the i-th grid cell, GRD i represents the road network density of the i-th grid cell;

[0052] Step 3: The flash flood risk index within the grid represents the comprehensive level of vulnerability of the disaster-bearing objects and the hazard of the disaster-causing objects in the area. The calculation method is as follows:

[0053] GFR = DI i ×TI i

[0054] Where TI i Represents the disaster index of the i-th grid unit, DI i Represents the disaster index of the i-th grid cell.

[0055] The above description of the disclosed embodiments is intended to enable one skilled in the art to implement or use the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention is not limited to the embodiments shown in this embodiment, but is intended to be construed in the widest manner consistent with the principles and novel features disclosed herein.

Claims

1. A flood risk measurement method that takes into account the water collection effect of the surrounding terrain of a mountain city, characterized by , the steps are as follows: Step 1: Based on high-resolution remote sensing image data, spatial analysis methods are used to construct buffer zones and accurately define urban catchment boundaries; Step 2: Use digital elevation model (DEM) and hydrological analysis tools to extract the runoff network of the mountains around the city and vectorize the river network data to improve the accuracy of the basin's hydrological information; Step 3: Combine urban boundary and river network information, identify potential flash flood discharge points and determine water discharge paths through terrain analysis and hydrological modeling technology; Step 4: Divide the study area into several spatial grid units, use the spatial distance measurement method to calculate the shortest distance from each grid to the dumping point, and assign the dumping point risk level based on the terrain and catchment conditions; Step five: Comprehensively consider the disaster-causing factors and disaster-bearing capacity of each grid unit, calculate the disaster-causing index and disaster-bearing index of flash flood disasters, and then build a systematic urban flash flood risk assessment framework.

2. A flood risk measurement method taking into account the water collection effect of the surrounding terrain of a mountain city according to claim 1, characterized in that: In step 1, boundary delineation methods include visual interpretation of high-resolution remote sensing images, DEM slope extraction and screening, and buffer zone boundary establishment.

3. A flood risk measurement method taking into account the water collection effect of the surrounding terrain of a mountain city according to claim 1, characterized in that: In step 2, the extracted river network information includes runoff direction, runoff flow, and runoff grade.

4. A flood risk measurement method taking into account the water collection effect of the surrounding terrain of a mountain city according to claim 1, characterized in that: The disaster index in step 5 is the flood risk of a grid unit when a flash flood occurs. The disaster index DI i The specific calculation formula is: In the formula, E n Represents the dumping level of the nth dumping point, L n Represents the distance from the grid cell to the nth dump point.

5. Disaster Susceptibility Index TI i is the comprehensive vulnerability of a grid unit to floods, including road network density (GRD), building density (BD), and POI density (GPD). The specific calculation formula is: THE i (GPD i ×0.4+GBD i ×0.2+GRD i ×0.4) The grid road network average density (GRD) is an indicator to measure the distribution of the road network. The specific calculation formula is: Where ∑R i is the sum of the road lengths within a single grid cell, and S is the area of ​​the grid cell Grid unit building density (GBD) refers to the number of buildings in each grid unit to measure the density of building distribution. The specific calculation formula is: Grid unit POI density (GPD) refers to the number density of a specific point of interest in a specific area in geographic space. The specific calculation formula is:

6. A flood risk measurement method taking into account the water collection effect of the surrounding terrain of a mountain city according to claim 1, characterized in that: In step 5, the flash flood risk (GFR) in the grid area of ​​the flash flood risk measurement system is constructed. The flash flood risk (GFR) in the grid area refers to the possibility of floods and their potential damage in a specific area. The specific calculation formula is: GFR=DI i ×IT i 。

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