CN116882741A - Method for dynamically and quantitatively evaluating super-standard flood disasters - Google Patents
Method for dynamically and quantitatively evaluating super-standard flood disasters Download PDFInfo
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Abstract
The invention discloses a method for dynamically and quantitatively evaluating a super-standard flood disaster, which comprises the following steps: step 1, acquiring basic data of a research area; step 2, performing super-standard flood real-time dynamic simulation by using a two-dimensional hydrodynamic model based on GPU heterogeneous parallel acceleration; step 3, constructing the spatial distribution of the socioeconomic class data and establishing association with flood inundation characteristic parameters; step 4, calculating and establishing the relation between flood inundation characteristic parameters and various property flood damage rates; and 5, estimating the loss of the over-standard flood disasters. The method realizes real-time dynamic rapid quantitative assessment of the flood disaster exceeding the standard of the flood disaster, improves timeliness and accuracy of the flood disaster assessment, and provides references for the exceeding the standard flood dispatching decision and real-time coping; and the GPU heterogeneous parallel acceleration method is adopted to reconstruct a two-dimensional hydrodynamic model, so that the consumption of computing resources is greatly reduced, and the computing efficiency of the model is improved.
Description
Technical Field
The invention belongs to the technical field of flood disaster assessment, and particularly relates to a dynamic quantitative assessment method for a super-standard flood disaster.
Background
Because of wider submerged range and higher risk of the super-standard flood, the range and the type of disaster-bearing bodies which are possibly affected are wider, and the disaster severity and the risk are essentially different from those of the flood in the standard, as shown in figure 1.
The traditional flood disaster evaluation mostly carries out data statistics and reporting by places after the occurrence of the disaster, lacks the pre-evaluation before the occurrence of the flood event and the real-time dynamic evaluation in the occurrence process of the flood disaster, and the original evaluation method and means cannot adapt to the characteristics of wide range of the super-standard flood inundation, strong risk, serious influence on various disaster-bearing bodies and the like. Therefore, it is important to regulate and control the risk of the over-standard flood in the occurrence process of the flood disaster and to take comprehensive emergency measures for reducing and avoiding disaster loss. The real-time dynamic assessment of the super-standard flood disasters can provide real-time information of flood influence and disaster loss under the condition of dispatching and application for decision makers, and is an important basis and technical means for engineering dispatching, risk regulation and control and measures taking. However, at present, the technical method for evaluating the hyperscale flood disasters is difficult to effectively support the actual demands of the watershed on the aspects of hyperscale flood regulation, comprehensive emergency management and the like in terms of timeliness, accuracy and the like. Therefore, a method for dynamically and quantitatively evaluating the super-standard flood disasters is needed in order to realize the real-time dynamic and rapid quantitative evaluation of the river basin super-standard flood disasters, and provide references for super-standard flood dispatching decisions and real-time coping.
Disclosure of Invention
The invention aims to provide a dynamic quantitative assessment method for a super-standard flood disaster, so as to solve the technical problems.
The invention is realized by the following technical scheme:
the invention discloses a method for dynamically and quantitatively evaluating an over-standard flood disaster, which comprises the following steps:
step 1, acquiring basic data of a research area: acquiring meteorological data, hydrological data, basic topography data, river section data, hydraulic engineering data, disaster bearing body data, socioeconomic data and space geographic information data of a research area;
step 2, performing super-standard flood real-time dynamic simulation by using a two-dimensional hydrodynamic model based on GPU heterogeneous parallel acceleration: according to the acquired meteorological data, hydrological data, basic topography data, river section data and hydraulic engineering data, a one-dimensional hydrodynamic model is utilized for river flood evolution analysis, a limited volume method is adopted, tight coupling of different water units is considered, and a river flood evolution process and a water level flow process of a concerned section are simulated; after one-dimensional river course is used for flood inundation analysis of the river basin surface by utilizing a two-dimensional hydrodynamic model, a two-dimensional finite volume method is adopted for model solving, the influence of different structures is considered, and flood inundation evolution calculation is carried out, so that flood inundation characteristic parameters are obtained; reconstructing a two-dimensional hydrodynamic model by adopting a GPU heterogeneous parallel acceleration method, and realizing parallel simulation of space, time and subprocesses by constructing a parallel computing system and dynamically distributing computing resources;
step 3, constructing the spatial distribution of the socioeconomic class data and establishing association with flood inundation characteristic parameters: according to the obtained socioeconomic data and the spatial geographic information data, establishing association between the socioeconomic data and the corresponding spatial image layer, reflecting the spatial distribution difference of the socioeconomic data, and forming the spatial distribution of the socioeconomic data; according to the obtained flood inundation characteristic parameters, carrying out topological superposition on the flood inundation characteristic distribution and the spatial distribution of the socioeconomic class data through a spatial geographic relation, and obtaining socioeconomic class data distribution under different flood inundation characteristic parameters within the flood influence range;
step 4, establishing the relation between flood inundation characteristic parameters and various property flood damage rates: selecting a certain number of areas, units or departments in a research area to carry out flood damage investigation and statistics, and establishing the relation between flood flooding characteristic parameters and flood damage rates of various properties according to different areas and disaster bearing body categories;
step 5, estimating the loss of the super-standard flood disasters: after determining the flooding degree and the pre-disaster value of various disaster-bearing bodies, classifying and estimating the hyperscale flood disaster loss according to the relation between the various disaster-bearing bodies and the flood disaster loss rate in the influence area.
Further, in the step 1, the meteorological data, hydrological data, basic topography data, river section data and hydraulic engineering data are provided by a meteorological office and a hydrological office or obtained by actual measurement; the disaster-bearing body data and the socioeconomic data are obtained through social investigation statistics; and the space geographic information material is obtained through GIS.
Further, the weather data in step 1 includes rainfall and evaporation data; the hydrologic data comprise hydrologic, water level site distribution and actual measurement hydrologic data; the basic topography data comprise full-element DLG vector layer and DEM data comprising elevation, residential land, river basin water system and vegetation layer; the river section data comprise actual measurement data of the longitudinal section and the transverse section of the current river; the hydraulic engineering data comprise reservoir, embankment and gate dam data; the disaster-bearing body data comprise land data of urban and rural residences, cultivated lands and industrial and commercial enterprises; the socioeconomic data includes population, GDP, floor space, cultivated land area, number of industrial and commercial enterprises, family property, agricultural output value, industrial and mining enterprise fixed asset and mobile asset data.
Further, the one-dimensional hydrodynamic model basic equation in step 2 includes a continuous equation and a momentum equation:
wherein, the continuous equation is:
the momentum equation is:
wherein: a is the water passing area of a river channel; q is flow; q is the lateral flow of the river course; t is time; x is a horizontal coordinate along the water flow direction; y is the water level; alpha is a momentum correction coefficient; g is gravity acceleration; s is S f Is friction resistance slope reduction; u is the flow velocity of the lateral incoming flow in the river direction;
the two-dimensional hydrodynamic model control equation adopts a conservation type two-dimensional shallow water equation:
U t +E(U) x +H(U) y ＝S 0 +S
wherein h is the water depth; u is the flow velocity in the x direction; v is the flow velocity in the y direction; p is p a Is the atmospheric pressure of the water surface; z b Is the elevation of the bed surface bottom; c x ，c y To convert the ground to coriolis force; τ bx ，τ by Is the cutting stress of the bed surface; τ ax ，τ ay The expression is as follows:
wherein ρ is a Is air density;is the wind speed at 10m above the water surface; c (C) Ds Is the drag coefficient.
Further, the flood inundation characteristic parameters in the step 2 include flood inundation area, inundation depth, inundation duration, flood flow rate and arrival time.
Further, in the step 2, the GPU heterogeneous parallel acceleration method is adopted to reconstruct a two-dimensional hydrodynamic model, and the specific process of realizing parallel simulation of space, time and sub-process is as follows:
1) Constructing a parallel computing system:
the parallel computing system comprises a server side, a client side and a node monitoring module, wherein the server side is used for receiving different computing task applications sent by a plurality of client sides and allocating available computing nodes to the client sides; the client is in charge of processing input and output data receiving and transmitting processing of the current computing task and is communicated with the node monitoring modules on all the computing nodes; the node monitoring module monitors the execution condition of a calculation program running on the node;
2) Dynamic allocation of computing resources:
for a computing task to be executed, packaging the computing task into an executable program of a single computing thread, and arranging the executable program on all computing nodes in advance; setting a node monitoring module at each node, and calling a plurality of calculation programs in parallel to work by adopting a process dynamic allocation technology;
the specific implementation steps are as follows: the client side remotely invokes a node monitoring module on a computing node participating in the computing task through an MPICH parallel computing command; the node monitoring module reads the number of processing cores of the node CPU processor in real time, starts a corresponding number of calculation programs to execute in parallel according to the number of the CPU cores, monitors the running states of all the calculation programs on the current node in real time, and returns the calculation states of the current node to the client through a TCP/IP network communication protocol; the client is responsible for collecting the state return values of all nodes participating in the calculation task, carrying out statistical analysis on the calculation result, and reporting the result of the calculation task to the server;
3) Parallel computing configuration:
constructing and realizing parallel simulation and parallel scheduling of a flood calculation kernel;
the parallel simulation is to realize parallel simulation from space, time and subprocess; the space parallel simulation is as follows: the model comprises a plurality of watercourses and a plurality of simulation units, and on the basis of considering the calculation dependency relationship among the simulation units, the calculation tasks of different simulation units are distributed to the plurality of calculation units to perform parallel calculation in a space decomposition mode; the time parallel simulation is as follows: flood simulation is performed at a plurality of moments in a continuous time sequence, and the output of the last moment is used as the input of the next moment;
the parallel scheduling is to design a parallel scheduling algorithm, and the real-time continuous simulation requirement is met.
The beneficial effects of the invention are as follows: the method is based on real-time forecast or actual rainfall flood information, realizes real-time dynamic rapid quantitative assessment of the flow field super-standard flood disasters through a two-dimensional hydrodynamic coupling model, improves timeliness and accuracy of flood disaster assessment, and provides references for super-standard flood scheduling decisions and real-time coping; and a two-dimensional hydrodynamic model is reconstructed by adopting a GPU heterogeneous parallel acceleration method, and the parallel simulation of space, time and sub-processes is realized by constructing a parallel computing system and dynamically distributing computing resources, so that the computing resource consumption is greatly reduced, and the computing efficiency of the model is improved.
The invention is described in further detail below with reference to the drawings and the detailed description.
Drawings
FIG. 1 is a diagram of a change in risk of a hyperscale flood disaster;
FIG. 2 is a flow chart of the method of the present invention;
FIG. 3 is a schematic diagram of a two-dimensional hydrodynamic model lateral connection;
FIG. 4 is a schematic diagram of a GIS expression pattern of a socioeconomic performance indicator;
FIG. 5 is a schematic view of a two-dimensional hydrodynamic model range in accordance with the first embodiment;
FIG. 6 is a diagram showing a flood diversion process in 1998 year 200 in one embodiment;
FIG. 7 is a diagram showing the flooding process in the river-crossing flood diversion area of 200 years in 1998;
FIG. 8 is a diagram showing a flood diversion process in 1998 year 1000 in first embodiment;
FIG. 9 is a diagram showing the flooding process of the river-crossing flood diversion area under 1000 years of 1998 flood in example I;
FIG. 10 is a diagram showing a flood diversion process in 1954 in 1000 years;
FIG. 11 is a diagram showing the flooding process in the river-crossing flood diversion area of 1000 years in 1954.
Detailed Description
The invention provides a method for dynamically and quantitatively evaluating an over-standard flood disaster, which is shown in fig. 2 and comprises the following steps:
and step 1, acquiring basic data of a research area.
Acquiring meteorological data, hydrological data, basic topography data, river section data, hydraulic engineering data, disaster bearing body data, socioeconomic data and space geographic information data of a research area; the meteorological data, the hydrologic data, the basic topography data, the river section data and the hydraulic engineering data are provided by a meteorological office and a hydrologic office or obtained by actual measurement and are used for real-time dynamic simulation of the super-standard flood; the disaster-bearing body data and the socioeconomic data are obtained through social investigation and statistics and are used for evaluating the super-standard flood disasters; and the space geographic information material is obtained through GIS.
The meteorological data comprise rainfall data, evaporation data and the like, the hydrologic data comprise hydrologic data, water level site distribution data, actual measurement hydrologic data and the like, the basic topographic map data comprise full-element DLG vector map layers including map layers of elevations, residential lands, river basin water systems, vegetation and the like, DEM data and the like, the river section data comprise actual measurement data of current river longitudinal and transverse sections and the like, and the hydraulic engineering data comprise reservoir, embankment, gate dam data and the like; the disaster-bearing body data comprise land data of urban and rural residences, cultivated lands, industrial and commercial enterprises and the like; the socioeconomic data comprises population, GDP, house area, cultivated land area, industrial and commercial enterprises number, family property, agricultural production value, industrial and mining enterprises fixed asset and mobile asset data and the like. Specifically, the results are shown in Table 1.
TABLE 1
And 2, performing real-time dynamic simulation of the super-standard flood by using a two-dimensional hydrodynamic model based on the heterogeneous parallel acceleration of the GPU.
According to the acquired meteorological data, hydrological data, basic topography data, river section data and hydraulic engineering data, a one-dimensional hydrodynamic model is utilized for river flood evolution analysis, a limited volume method suitable for a steep slope river is adopted, the method has the capability of simulating engineering application of river gates, dams and the like, the practicability of the river model is improved, the tight coupling of different water units such as dry branches and the like is considered, a river flood evolution process and a water level flow process of a focused section are simulated, and a flood water level process and a flood flow process of a river section are obtained; after one-dimensional river channel is used for flood inundation analysis of the surface of a river basin by utilizing a two-dimensional hydrodynamic model, rapid flood calculation of complex terrain conditions and large gradient or shock wave discontinuous water flow conditions can be performed, a two-dimensional finite volume method is adopted for model solving, and the influences of different structures such as a weir gate, a road and the like are considered for flood inundation evolution calculation, so that flood inundation characteristic parameters including flood inundation area, inundation depth, inundation duration, flood flow rate and arrival time are obtained. And reconstructing a two-dimensional hydrodynamic model by adopting a GPU heterogeneous parallel acceleration method, constructing and dynamically distributing computing resources by a parallel computing system, realizing parallel simulation of space, time and subprocesses, greatly reducing computing resource consumption and improving model computing efficiency.
Specifically, the one-dimensional hydrodynamic model basic equation includes a continuous equation and a momentum equation.
Wherein, the continuous equation is:
the momentum equation is:
wherein: a is the water passing area of a river channel; q is flow; q is the lateral flow of the river course; t is time; x is a horizontal coordinate along the water flow direction; y is the water level; alpha is a momentum correction coefficient; g is gravity acceleration; s is S f Is friction resistance slope reduction; u is the flow velocity of the lateral incoming flow in the direction of the river.
The equation set adopts four-point Prinesmann hidden format solution, and simultaneously, in order to avoid the problems of complex hidden format solution, troublesome boundary condition processing and hydraulic engineering adding, the model also provides an integral form adopting an LAX format, a mode of arranging water levels in the middle of a flow section on the section is adopted for flow and water level variables, after the flow is obtained through a difference method, a finite volume method is adopted for processing and solving the water level of a continuous equation, and the physical significance is clear.
The upper boundary condition of river channel flood is preferably to adopt the actual flood flow process or the designed flood flow process of the upstream of the river where the calculation area is located, and when the control engineering exists on the upstream, the designed lower discharge flow process is adopted; the lower boundary condition can be the downstream water level-flow relation, or the scheduling rule of the control hydraulic engineering, etc. When the data is not available, the Manning formula is adopted to calculate and determine the lower boundary condition approximately outside at least five section distances of the river channel at the downstream of the calculation region.
The two-dimensional hydrodynamic model control equation adopts a conservation type two-dimensional shallow water equation:
U t +E(U) x +H(U) y ＝S 0 +S
wherein h is the water depth; u is the flow velocity in the x direction; v is the flow velocity in the y direction; p is p a Is the atmospheric pressure of the water surface; z b Is the elevation of the bed surface bottom; c x ，c y To convert the ground to coriolis force; τ bx ，τ by Is the cutting stress of the bed surface; τ ax ，τ ay The expression is as follows:
wherein ρ is a Is air density;is the wind speed at 10m above the water surface; c (C) Ds Is the drag coefficient.
The two-dimensional flood simulation model system adopts a Godunov algorithm to carry out numerical calculation, wherein the Riemann problem adopts an approximate Riemann solution in a Roe format to carry out calculation, a bottom slope source item adopts characteristic grading dispersion to ensure conservation of the model, a resistance source item adopts implicit dispersion to improve stability of the model, a variable is defined in a calculation grid center, and a MUSCL space reconstruction and prediction correction method is adopted to enable the model to have time and space second order precision.
In river numerical simulation, the upstream flood water supply level boundary is usually given by the upstream flood water supply boundary condition or the single wide flood water supply boundary condition. According to the direction of the characteristic line, boundary water flow is divided into three conditions of slow flow, outflow rapid flow and inflow rapid flow, under the condition of rapid flow inflow, the information in a calculation area cannot influence the boundary, and all unknown variables need to be given on the boundary; under the condition of the rapid flow outflow, the out-of-boundary information cannot influence the calculation area, so that any boundary condition is not required to be given; in the case of sluggish flow, at least one given boundary condition (water depth or flow rate) is required to be able to calculate the boundary variables.
The coupling of the earth surface two-dimensional hydrodynamic model is realized by adopting lateral connection, the water flow exchange problem of the lateral connection is calculated by using the most extensive weir flow formula method, the lateral connection, namely a river channel carries out water flow exchange with a two-dimensional model calculation area through two sides, and the key point of processing the connection type is to calculate the exchange water quantity of the two models at the coupling boundary. As shown in fig. 3, the joint solution of the two-dimensional model is realized by a lateral connection mode, and after one-dimensional river channel is used for flood evolution, a two-dimensional flood evolution process of the submerged area is generated.
In order to realize the rapid assessment of the super-standard flood disasters, a GPU heterogeneous parallel acceleration method is adopted to reconstruct a two-dimensional hydrodynamic model, and the parallel simulation of space, time and sub-processes is realized through the construction of a parallel computing system and the dynamic distribution of computing resources, so that the computing resource consumption is greatly reduced, and the computing efficiency of the model is improved.
1) Building parallel computing systems
A cluster is an aggregate of a group of independent computers (nodes) connected by a high-performance network, each node can be used as a single computing resource for interactive users, and can also cooperate and represent a single and centralized computing resource for parallel computing. A cluster is a low cost, easy to build, and well scalable parallel architecture. Therefore, by adopting a strategy of building the cluster system, computers with different performances in clients can be incorporated into the cluster system.
The method comprises the steps of setting a server side, receiving different computing task applications sent by a plurality of clients, and allocating available computing nodes to the clients;
setting a client, namely, carrying out receiving and transmitting processing on input and output data for processing the calculation task, and communicating with a node monitoring module on each calculation node;
setting a node monitoring module for monitoring the execution condition of a calculation program running on the node;
and the computing program is responsible for executing specific computing tasks.
2) Dynamic allocation of computing resources
For such a computing task, the computing task can be packaged into an executable program of a single computing thread and is arranged on all computing nodes in advance; and setting a node monitoring module at each node, and calling a plurality of calculation programs in parallel by adopting a process dynamic allocation technology.
The specific implementation steps are as follows:
the client side remotely invokes a node monitoring module on a computing node participating in the computing task through an MPICH parallel computing command;
the node monitoring module reads the number of processing cores of the node CPU processor in real time, and starts a corresponding number of calculation programs to execute in parallel according to the number of the CPU cores; monitoring the running states of all calculation programs on the current node in real time; the calculation state of the current node is returned to the client through a TCP/IP network communication protocol;
the client is in charge of collecting state return values of all nodes participating in the calculation task, and then carrying out statistical analysis on the calculation result; and reporting the result of the calculation task to the server side.
In summary, assuming that 1 computing task has X computing nodes to participate, and the number of CPU cores of each computing node is Y, XY computing programs can be executed in parallel at the same time, which is XY times the single-thread execution efficiency.
3) Parallel computing configuration
The parallel simulation and the parallel scheduling of the flood calculation kernel are constructed and realized, so that the flood analysis calculation time is effectively reduced, and the efficiency of mass data interaction is improved.
(1) Parallel simulation
Parallel simulation from space, time and sub-processes is achieved. The space may be parallel: the model comprises a plurality of watercourses and a plurality of simulation units (slope surfaces and grids), and the calculation tasks of different simulation units are distributed to a plurality of calculation units to perform parallel calculation in a space decomposition mode on the basis of considering the calculation dependency relationship among the simulation units. The time may be parallel: from a time perspective, the flood simulation is performed at a plurality of moments in a continuous time sequence, with the output of the last moment being the input of the next moment.
(2) Parallel scheduling
The parallel scheduling algorithm aims at 'low resource consumption and high calculation efficiency', and an effective and stable parallel scheduling algorithm is designed to meet the requirement of real-time continuous simulation. The server side and the client side realize asynchronous TCP/IP technology.
And 3, constructing the spatial distribution of the socioeconomic class data and establishing association with flood inundation characteristic parameters.
According to the obtained socioeconomic data and the spatial geographic information data, establishing association between the socioeconomic data and the corresponding spatial image layer, reflecting the spatial distribution difference of the socioeconomic data, and forming the spatial distribution of the socioeconomic data; and carrying out topological superposition on the flood inundation characteristic distribution and the spatial distribution of the socioeconomic class data through a spatial geographic relation according to the obtained flood inundation characteristic parameters, and obtaining the socioeconomic class data distribution under different flood inundation characteristic parameters within the flood influence range.
Flood disaster damage assessment involves a large amount of spatial data, whether flood intensity distribution or socioeconomic information of flooded areas, should have spatial attributes. Usually, the collected economic statistical data such as population, economic industry development and the like are stored in a non-spatial data mode, namely, the data are collected, summarized and released through administrative units in county and area (villages and towns), the data do not point to the corresponding ground object, the spatial difference inside the statistical unit is difficult to embody, and in order to better evaluate the influence of flood disasters, the spatial difference characteristics need to be restored or rebuilt.
By means of GIS technology, various types of statistical indicators can be defined on the corresponding vector diagram layer, such as limiting population distribution ranges to populated areas, locating planting industry production values to cultivated areas, locating industrial assets to industrial areas, etc. As shown in FIG. 4, the GIS expression mode of the socioeconomic index is shown, each index can be discretized within the defined unit range, and can be continuously distributed in a certain unit, namely, each spatial position corresponds to a value of a spatial variable, and can be generalized to be uniformly distributed or still have spatial difference in a (statistical) unit.
And comprehensively analyzing and evaluating the influence degree of flood according to flood inundation characteristic parameters obtained by flood analysis of a research area and combining with social and economic conditions in a inundation area, wherein the flood inundation characteristic parameters comprise the areas of inundated administrative areas, the areas of inundated residents, the areas of inundated cultivated lands, the numbers of inundated key units, the affected population, GDP and the like in different inundated water depth areas in the inundation area.
1) Statistics of area of flooded administrative area, flooded residential area and flooded cultivated area
And based on the superposition analysis function of GIS software, respectively superposing the submerged map layer with the administrative region map layer, the cultivated map layer and the resident map layer to obtain the submerged administrative region area, the submerged resident area, the submerged cultivated area and the like under corresponding different submerged water depth grades.
2) Statistics of flooded key units
The key units are generally distributed in a punctiform manner on the GIS layer. And after obtaining flood inundation characteristic parameters, performing space superposition operation on the inundation layer, the administrative region layer and the key single-bitmap layer, namely, performing superposition operation on the surface layer and the dot map layer to obtain the key unit quantity, specific distribution condition and related attribute information of the inundation region. According to the data collection condition, determining the flooded key units mainly comprises the following steps: factories, schools, hospitals, administrative offices, warehouses, business enterprises, and the like.
3) Statistics of affected population
The affected population is indirectly derived from the area of the affected population within the inundation. Firstly, estimating the number of affected households according to the total area of the affected residents, then obtaining the average number of residents in towns (villages) according to population data in the statistical annual views of all the cities, and further estimating the affected population:
4) Statistics of affected GDP
The affected GDP may be calculated according to the human or ground average GDP method. The average person GDP method calculates the affected GDP according to the multiplication of the affected population of a certain administrative area and the average person GDP of the administrative area; the ground average GDP rule is to calculate the affected GDP by multiplying the area of the flooded area of the different administrative units by the GDP value per unit area of the administrative area.
And 4, establishing a relation between flood inundation characteristic parameters and various property flood damage rates.
And selecting a certain number of representative areas, units, departments and the like as flood damage investigation statistics in the research area, estimating various property flood damage rates under different flood flooding characteristic parameters according to investigation data, and establishing the relationship between the flood flooding characteristic parameters and the various property flood damage rates, wherein the relationship can be a relationship curve or a relationship table. Flood damage indexes mainly comprise urban and rural resident family property damage, industrial and commercial enterprise damage, agricultural economic loss and the like.
With respect to loss rate determination, flood loss rate refers to the ratio of the value of various property losses to the value of various properties originally present in the pre-disaster or normal year. Factors influencing the loss rate of flood disaster are numerous, such as flooding characteristic parameters (including flooding depth, flooding duration, etc.), property types, disaster seasons, rescue measures, etc. Generally, a relation curve or a relation table of flood loss rate and flood characteristic parameters is respectively established according to different areas and disaster-bearing body types. In order to analyze the flood damage rate of various flood grades and various properties in a research area, a certain number of representative areas with a certain scale are selected for investigation in a flood area (a place which is subjected to flood in recent years in a similar area). On the basis of field investigation, the method is combined into disaster seasons, ranges, flood forestation periods, rescue time, rescue measures and the like, and the correlation between the flood loss rate and flood inundation characteristic parameters is established.
And 5, estimating the loss of the over-standard flood disasters.
After determining the flooding degree and the pre-disaster value of various disaster-bearing bodies, classifying and estimating the hyperscale flood disaster loss according to the relation between various disaster-bearing bodies and the flood disaster loss rate in the influence area.
Flood loss categories are often divided into: urban and rural resident family property loss, industrial and commercial enterprise loss, agricultural economic loss and the like. The calculation method of each direct economic loss category is as follows:
1) And (5) calculating the household property loss of urban and rural residents:
the calculation formula of the direct loss value of urban and rural resident family property is as follows:
wherein R is rc The method is a direct loss value of the flood of the family property of urban and rural residents, and is a meta; r is R rcu The method is a direct loss value of urban household property flood, and is a meta-value; r is R rcr The method is a rural resident family property loss value; w (W) ui For the value before disaster of the family property of the urban residents under the level i submerged depth, the value is meta/km 2 ；W ri For the value before disaster of the family property of rural residents under the i-th level submerged water depth, yuan/km 2 ；S ui For the area of the flooded house of the urban residents under the i-th level of submerged water depth, km 2 ；S ri Is the area of the flooded house of the rural residents under the i-th level submerged water depth, km 2 ；η i The loss rate of flood damage of urban and rural family property is%; n is the number of submerged water depth levels.
2) And (5) calculating the loss of an industrial enterprise:
when calculating various property losses of industrial and commercial enterprises, fixed assets (including factory buildings, offices, business rooms, production equipment, transportation tools and the like) and mobile assets (including raw materials, finished products, semi-finished products, inventory materials and the like) need to be considered respectively, and the calculation formula is as follows:
wherein R is ur The method is a flood disaster property total loss value of industrial and commercial enterprises; r is R urf Fixing asset loss values and elements for flood disasters of industrial and commercial enterprises; r is R urc The loss value of the flood mobile asset for the business enterprise is calculated; w (W) fi Fixing resource values, yuan/units for enterprises under the ith submerged water depth level; w (W) ci The method comprises the steps of (1) setting a mobile asset value, element/element for an enterprise under the level i submerged water depth; s is S uri The number of submerged industrial and commercial enterprises is the number of the submerged industrial and commercial enterprises under the i-th submerged water depth; η (eta) i Fixed asset flood loss rate,%; beta i The loss rate of the mobile asset flood of the business enterprise is calculated for the i-th submerged depth,%; n is the number of submerged water depth levels.
3) Agricultural economic loss calculation:
wherein R is a Is a direct economic loss of agriculture; w (W) ai For the total agricultural yield value under the i-th level submerged water depth, yuan/km 2 ；S ai Is the area of the flooded cultivated land under the i-th level of submerged water depth, km 2 ；η i Loss rate of agricultural yield under the level i submerged depth,%; n is the number of submerged water depth levels.
4) Total economic loss calculation
As described above, the calculation method of the property loss value of each type includes that the total loss of each administrative area includes family property, family housing, business enterprise and agriculture, and the economic total loss of the affected area is obtained by accumulating the losses of each administrative area, and the calculation formula is as follows:
wherein R is i The total value of various losses of the ith administrative division is calculated; r is R ij A j-th class loss value in the i-th administrative partition, and a meta; k, the number of administrative divisions; m, the number of lost species.
Example 1
The present embodiment is a specific application example of the above method.
The Jingjiang river section of the Yangtze river at the flood diversion area of the Jingjiang river is located in the public security county of Hubei province, the northeast is in the face of the Yangjiang river, the south is against the Anxiang river, borders with the Anxiang county of Hunan province, and the West is in the way of tiger ferry. The length of the north and south is 70km, the east-west average width is 13km, the narrow neck is 2.7km, the topography north is high and south is low in the area, and the ground elevation is 34.00-39.00 m (freezing Wu Songgao journey, the same applies below). Jingjiang flood diversion area was built in 1952 and total area was 921.34km 2 The flood storage water level (gold mouth) is designed to be 42.00m, and the flood storage capacity is designed to be 54 hundred million m 3 Flood diversion flow 7700m 3 And/s. When the water level of the three gorges reservoir is higher than 171.0m, the water coming from the upstream is still large, and the discharge flow of the reservoir is gradually increased to control the flow of the branch and city station to be no more than 80000m 3 In order to control the water level of the water station of the water market not to exceed 45m, the water storage flood area of the Jingjiang region is matched with the water storage flood area, and when the water level of the water station of the water market cannot be controlled to rise, then the rear gate of the river levee entrance in the expanded area of the city of blasting and the east and west levees of the inner first side of the tiger ferry are combined with the flood diversion area of Jingjiang to control the discharge flow at the same time at the upper and lower sides by using the throttle gate (south gate) of the tiger ferry, and the maximum is not more than 3800m 3 And/s, simultaneously preparing for the joint operation of the tiger west preparation storage area and the Jingjiang flood diversion area, and forecasting that the flood storage water level (golden mouth station, the same applies below) in the Jingjiang flood diversion area is more than 42.00 meters, and blasting the tiger east dyke and the tiger west dyke to ensure that the tiger west preparation storage area and the Jingjiang flood diversion area are jointly operated.
Constructing a one-dimensional and two-dimensional hydrodynamic coupling model, wherein the one-dimensional model ranges from branch city to supervision, and the two-dimensional model comprises a Jingjiang flood diversion area, a city expansion flood diversion area and tigersThe total of the western reserve storage area is 1103.34km 2 The model range is shown in fig. 5. In the two-dimensional model, 30530 fine grids with average space step length of 200m are adopted in the fine simulation, 5520 coarse grids with average space step length of 500m are adopted in the quick simulation, the model is set as a flow inflow boundary at a gate in the north of a Jingjiang flood diversion area, a gate in a Yanglin flood diversion area and a gate in an enlarged flood diversion area of city, an outflow boundary is set at a gate in a south of a tiger, a gate in a Jingjiang flood storage area and a gate in a dyke in a duan river, and an internal control boundary is set at two positions of a gate in a river of a tiger and a zodiac-Jiang mouth. The one-dimensional model is coupled at the north gate of Jingjiang flood diversion area, the gate of wax Lin Zhoujiang dyke flood diversion area, the no-dose-land Jiang Dikou gate of Jingjiang flood diversion area and the gate of the extended flood diversion area at city.
And (3) carrying out dynamic quantitative assessment on the super-standard flood disasters by using the flood risk map analysis results and adopting the following three design working conditions.
1) When the water level of the sandy city reaches 45.0m and the rising is predicted to continue, the flood diversion process of the north floodgate is started in 200 th year of 1998, as shown in figure 6.
Under the condition of the rapid simulation of the refined grid, the flood inundation condition process diagram calculated by adopting the working conditions is shown in fig. 7, and the disaster loss evaluation result is shown in table 2.
TABLE 2
2) Under the condition that the water level of the sandy city reaches 45.0m in 1000 th 1998 and the rising is predicted, starting the north gate, and if the rising of the water level of the sandy city cannot be controlled, blasting the Lab mountain gate and the whole flood diversion process of the Jingjiang flood diversion area is still carried out, as shown in figure 8.
Under the condition of the rapid simulation of the refined grid, the flood inundation condition process diagram calculated by adopting the working conditions is shown in fig. 9, and the disaster loss evaluation result is shown in table 3.
TABLE 3 Table 3
| Index (I) | 5h | 10h | 25h | 50h |
| Submerged area (km) 2 ) | 34.06 | 119.69 | 397.71 | 813.11 |
| Submerged area population (thousands of people) | 1.93 | 6.78 | 22.52 | 46.05 |
| Submerged region GDP (Wanyuan) | 33932.50 | 119227.40 | 396173.80 | 809969.90 |
| Loss of resident house (Wanyuan) | 39680.12 | 139422.50 | 463279.30 | 947165.70 |
| Family property loss (Wanyuan) | 9456.43 | 33226.70 | 110407.10 | 225725.30 |
| Agricultural loss (Wanyuan) | 13300.46 | 46733.33 | 155287.50 | 317482.40 |
| Industrial asset loss (Wanyuan) | 2055.81 | 7223.44 | 24002.35 | 49072.36 |
| Commercial and trade asset loss (Wanyuan) | 781.94 | 2747.48 | 9129.43 | 18664.95 |
| Aggregate (Wanyuan) | 66589.59 | 233973.30 | 777456.70 | 1589496.00 |
3) Under the condition that the water level of the water tank reaches 45.0m in 1000 th 1954, and when the water tank is predicted to continue rising, the north gate is started, if the water level of the water tank cannot be controlled to rise, the Lab-Hui gate is exploded, and the whole flood diversion process of the Jingjiang flood diversion area is shown in figure 10.
Under the condition of the rapid simulation of the refined grid, the flood inundation condition process diagram calculated by adopting the working conditions is shown in fig. 11, and the disaster loss evaluation result is shown in table 4.
TABLE 4 Table 4
Finally, it should be noted that the above description is only for the purpose of illustrating the technical solution of the present invention and not for the purpose of limiting the same, and that although the present invention has been described in detail with reference to the preferred arrangement, it will be understood by those skilled in the art that modifications and equivalents may be made thereto without departing from the spirit and scope of the technical solution of the present invention.
Claims (6)
1. A method for dynamically and quantitatively evaluating a hyperscale flood disaster, which is characterized by comprising the following steps of:
step 1, acquiring basic data of a research area: acquiring meteorological data, hydrological data, basic topography data, river section data, hydraulic engineering data, disaster bearing body data, socioeconomic data and space geographic information data of a research area;
step 2, performing super-standard flood real-time dynamic simulation by using a two-dimensional hydrodynamic model based on GPU heterogeneous parallel acceleration: according to the acquired meteorological data, hydrological data, basic topography data, river section data and hydraulic engineering data, a one-dimensional hydrodynamic model is utilized for river flood evolution analysis, a limited volume method is adopted, tight coupling of different water units is considered, and a river flood evolution process and a water level flow process of a concerned section are simulated; after one-dimensional river course is used for flood inundation analysis of the river basin surface by utilizing a two-dimensional hydrodynamic model, a two-dimensional finite volume method is adopted for model solving, the influence of different structures is considered, and flood inundation evolution calculation is carried out, so that flood inundation characteristic parameters are obtained; reconstructing a two-dimensional hydrodynamic model by adopting a GPU heterogeneous parallel acceleration method, and realizing parallel simulation of space, time and subprocesses by constructing a parallel computing system and dynamically distributing computing resources;
step 3, constructing the spatial distribution of the socioeconomic class data and establishing association with flood inundation characteristic parameters: according to the obtained socioeconomic data and the spatial geographic information data, establishing association between the socioeconomic data and the corresponding spatial image layer, reflecting the spatial distribution difference of the socioeconomic data, and forming the spatial distribution of the socioeconomic data; according to the obtained flood inundation characteristic parameters, carrying out topological superposition on the flood inundation characteristic distribution and the spatial distribution of the socioeconomic class data through a spatial geographic relation, and obtaining socioeconomic class data distribution under different flood inundation characteristic parameters within the flood influence range;
step 4, establishing the relation between flood inundation characteristic parameters and various property flood damage rates: selecting a certain number of areas, units or departments in a research area to carry out flood damage investigation and statistics, and establishing the relation between flood flooding characteristic parameters and flood damage rates of various properties according to different areas and disaster bearing body categories;
step 5, estimating the loss of the super-standard flood disasters: after determining the flooding degree and the pre-disaster value of various disaster-bearing bodies, classifying and estimating the hyperscale flood disaster loss according to the relation between the various disaster-bearing bodies and the flood disaster loss rate in the influence area.
2. The method for dynamically and quantitatively evaluating the super-standard flood disasters according to claim 1, wherein the meteorological data, hydrological data, basic topography data, river section data and hydraulic engineering data in the step 1 are provided by a meteorological bureau and a hydrological bureau or obtained by actual measurement; the disaster-bearing body data and the socioeconomic data are obtained through social investigation statistics; and the space geographic information material is obtained through GIS.
3. The method for dynamically and quantitatively evaluating the ultra-standard flood disasters according to claim 1, wherein the meteorological data in the step 1 comprises rainfall and evaporation data; the hydrologic data comprise hydrologic, water level site distribution and actual measurement hydrologic data; the basic topography data comprise full-element DLG vector layer and DEM data comprising elevation, residential land, river basin water system and vegetation layer; the river section data comprise actual measurement data of the longitudinal section and the transverse section of the current river; the hydraulic engineering data comprise reservoir, embankment and gate dam data; the disaster-bearing body data comprise land data of urban and rural residences, cultivated lands and industrial and commercial enterprises; the socioeconomic data includes population, GDP, floor space, cultivated land area, number of industrial and commercial enterprises, family property, agricultural output value, industrial and mining enterprise fixed asset and mobile asset data.
4. The method for dynamically and quantitatively evaluating the hyperscale flood disasters according to claim 1, wherein the one-dimensional hydrodynamic model basic equation in the step 2 comprises a continuous equation and a momentum equation:
wherein, the continuous equation is:
the momentum equation is:
wherein: a is the water passing area of a river channel; q is flow; q is the lateral flow of the river course; t is time; x is a horizontal coordinate along the water flow direction; y is the water level; alpha is a momentum correction coefficient; g is gravity acceleration; s is S f Is friction resistance slope reduction; u is the lateral incoming flow in the riverFlow velocity in the track direction;
the two-dimensional hydrodynamic model control equation adopts a conservation type two-dimensional shallow water equation:
U t +E(U) x +H(U) y ＝S 0 +S
wherein h is the water depth; u is the flow velocity in the x direction; v is the flow velocity in the y direction; p is p a Is the atmospheric pressure of the water surface; z b Is the elevation of the bed surface bottom; c x ，c y To convert the ground to coriolis force; τ bx ，τ by Is the cutting stress of the bed surface; τ ax ，τ ay The expression is as follows:
wherein ρ is a Is air density;is the wind speed at 10m above the water surface; c (C) Ds Is the drag coefficient.
5. The method according to claim 1, wherein the flood inundation characteristic parameters in the step 2 include flood inundation area, inundation depth, inundation duration, flood flow rate and arrival time.
6. The method for dynamically and quantitatively evaluating the super-standard flood disasters according to claim 1, wherein in the step 2, a two-dimensional hydrodynamic model is reconstructed by adopting a GPU heterogeneous parallel acceleration method, and the specific process of realizing parallel simulation of space, time and subprocesses by constructing and dynamically distributing computing resources through a parallel computing system is as follows:
1) Constructing a parallel computing system:
the parallel computing system comprises a server side, a client side and a node monitoring module, wherein the server side is used for receiving different computing task applications sent by a plurality of client sides and allocating available computing nodes to the client sides; the client is in charge of processing input and output data receiving and transmitting processing of the current computing task and is communicated with the node monitoring modules on all the computing nodes; the node monitoring module monitors the execution condition of a calculation program running on the node;
2) Dynamic allocation of computing resources:
for a computing task to be executed, packaging the computing task into an executable program of a single computing thread, and arranging the executable program on all computing nodes in advance; setting a node monitoring module at each node, and calling a plurality of calculation programs in parallel to work by adopting a process dynamic allocation technology;
the specific implementation steps are as follows: the client side remotely invokes a node monitoring module on a computing node participating in the computing task through an MPICH parallel computing command; the node monitoring module reads the number of processing cores of the node CPU processor in real time, starts a corresponding number of calculation programs to execute in parallel according to the number of the CPU cores, monitors the running states of all the calculation programs on the current node in real time, and returns the calculation states of the current node to the client through a TCP/IP network communication protocol; the client is responsible for collecting the state return values of all nodes participating in the calculation task, carrying out statistical analysis on the calculation result, and reporting the result of the calculation task to the server;
3) Parallel computing configuration:
constructing and realizing parallel simulation and parallel scheduling of a flood calculation kernel;
the parallel simulation is to realize parallel simulation from space, time and subprocess; the space parallel simulation is as follows: the model comprises a plurality of watercourses and a plurality of simulation units, and on the basis of considering the calculation dependency relationship among the simulation units, the calculation tasks of different simulation units are distributed to the plurality of calculation units to perform parallel calculation in a space decomposition mode; the time parallel simulation is as follows: flood simulation is performed at a plurality of moments in a continuous time sequence, and the output of the last moment is used as the input of the next moment;
the parallel scheduling is to design a parallel scheduling algorithm, and the real-time continuous simulation requirement is met.
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