CN114662736A - Mountain torrent disaster risk zoning and predicting method, system, equipment and terminal - Google Patents
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Abstract
The invention belongs to the technical field of natural disaster risk prediction, and discloses a mountain torrent disaster risk zoning and prediction method, a mountain torrent disaster risk zoning and prediction system, mountain torrent disaster risk zoning and prediction equipment and a terminal, which comprise: risk analysis based on village and town units; vulnerability analysis based on the village and town unit; risk zoning based on village and town units. The flood control system comprehensively considers factors such as drainage basin production convergence, river cross section and disaster water level, and can be used for representing the risk of disaster occurrence. Compared with the conventional risk assessment and division based on multi-factor superposition analysis, the method disclosed by the invention is based on the actual investigation result of the mountain torrent disaster dangerous area and the prevention and control requirements of the mountain torrent disaster, and adopts the towns smaller than the counties as the calculation units, so that the actual mountain torrent disaster risk level in a small range can be more clearly disclosed, the defect that the real condition of a local point is difficult to reflect by the on-plane prediction result obtained by superposition of disaster-causing factors is overcome, and the method is favorable for guiding local towns to make more effective mountain torrent disaster prevention plans according to the actual risk condition.
Description
Technical Field
The invention belongs to the technical field of natural disaster risk prediction, and particularly relates to a mountain torrent disaster risk zoning and prediction method, system, equipment and terminal.
Background
At present, mountain torrent disasters are common natural disasters in hilly areas and have the characteristics of strong outburst, high harmfulness, difficult early warning and the like. The method is necessary for reinforcing mountain torrent risk management and decision making, guiding mountain torrent disaster prevention and control and carrying out mountain torrent disaster risk zoning research. The concept of risk (risk) was first proposed in the western economic field at the end of the 19 th century and is now widely used in the fields of environmental science, nature, disasters, economics, sociology, architectural engineering, and the like. The risk definition accepted by most scholars and related institutions contains 3 aspects of meaning: adverse events, probability of occurrence and possible consequences. The risk assessment of the mountain torrent disaster is a precondition of risk division, and the mountain torrent disaster risk generally refers to an expected loss value of social and economic properties in a disaster process, and implies two contents of probability of disaster occurrence and loss possibly caused by the disaster. Based on the concept, according to the social and economic conditions of mountain torrent pregnancy disaster environments, disaster factors and disaster-bearing bodies, by means of a GIS technology, through data acquisition, spatial attribute database construction, evaluation index system selection, prediction evaluation analysis and the like, a relatively mature technical route and method system for mountain torrent disaster risk evaluation and risk zoning are established. Then, the method enters a wide application period, the wrinkle sensitivity researches mountain torrent disaster risk divisions in a yellow river basin by using a GIS evaluation technology, people in Tang dynasty and other schools analyze dynamic conditions, pregnant disaster environments and rainfall backgrounds formed by mountain torrent disasters, and the natural breakpoint classification method is used for dividing the mountain torrent disaster risk divisions into a high-emergence area, an easy-emergence area, a common area and a low-emergence area to finish the mountain torrent disaster divisions in Chongqing cities. The Zhang Qian column and other people utilize the mountain torrent disaster investigation evaluation data in 2013-2015 of Chongqing city, fuse multiple parameters such as rainfall conditions, underlying surfaces, population conditions, economic properties and the like, embed disaster resistance correction parameters, determine each index weight by an Analytic Hierarchy Process (AHP), establish a mountain torrent disaster risk evaluation index system of the Chongqing city, and further refine the mountain torrent disaster division of the Chongqing city. Dingwenfeng et al, based on GIS technology and national mountain torrent disaster prevention and treatment planning data, take Sichuan province as an example, and use natural disaster risk concept as a reference, quantify and analyze mountain torrent disaster risk, vulnerability and risk degree, and regionalize mountain torrent disaster risk in Sichuan province according to general principles of regionalization theory and first-level and second-level prevention and treatment zoning ranges of national mountain torrent disasters. The dividing mode is based on the macroscopic judgment of disaster causing factors on the occurrence probability and the loss of the mountain torrent disasters, and the dividing result has important guiding significance for predicting the development trend of the mountain torrent disasters and developing the defense work of the mountain torrent disasters to a certain extent. However, when disaster risk calculation is performed, hierarchical analysis and factor space superposition are often performed, and in the process, risk distortion and trend deformation occur to a great extent, because cross interference often exists between disaster-causing factors, which is not the concept of "1 +1 ═ 2". On the other hand, most of the mountain torrent disasters are natural disasters occurring at local points, and the on-plane prediction results obtained by superposing the disaster-causing factors are difficult to reflect the real conditions at the local points, and even a plurality of areas have no resident points, so that the mountain torrent disasters do not exist. The mountain torrent disaster early warning platform generally extends to villages and towns, namely the villages and the towns are basic units for carrying out mountain torrent disaster monitoring, early warning and emergency rescue and relief work, and for mountain torrent disaster defense work, a risk division taking the villages and the towns as units is easier to make and implement policies. Meanwhile, the mountain torrent disaster prevention and control work with villages and towns as units is basically developed around hidden danger points in the area, and when the mountain torrent disaster risk is analyzed, the mountain torrent disaster risk of the villages and the towns can be reflected according to the whole risk level of the hidden danger points. Therefore, it is desirable to design a method for disaster risk zoning and prediction of torrential floods.
Through the above analysis, the problems and defects of the prior art are as follows:
(1) when disaster risk calculation is performed, in the prior art, hierarchical analysis and factor space superposition are used for realizing the disaster risk calculation, risk distortion and trend deformation occur, cross interference exists among disaster causing factors, and the concept of "1 +1 ═ 2" is not provided.
(2) Most of mountain torrent disasters are natural disasters occurring at local points, and the on-plane prediction result obtained by superposing disaster-causing factors in the prior art is difficult to reflect the real situation at the local points.
The difficulty in solving the above problems and defects is: compared with the conventional mountain torrent disaster risk assessment and division based on multi-factor superposition, the method needs to perform investigation and evaluation of mountain torrent disaster points, and is easy to implement based on the existing mountain torrent disaster investigation and evaluation technical specifications.
The significance of solving the problems and the defects is as follows: the method is based on the actual investigation result of the mountain torrent disaster dangerous area, overcomes the defect that the real situation of the local point is difficult to reflect by the on-plane prediction result obtained by superposing the disaster causing factors, and is beneficial to guiding local villages and towns to make a more effective mountain torrent disaster prevention plan according to the actual risk situation.
Disclosure of Invention
Aiming at the problems in the prior art, the invention provides a method, a system, equipment and a terminal for mountain torrent disaster risk zoning and prediction.
The present invention is achieved in this way, and provides a mountain torrent disaster risk zoning and prediction method, including the steps of:
step one, risk analysis based on a village and town unit: the method comprises the steps of taking villages and towns as units, conducting investigation on hidden danger points of mountain flood disasters, measuring river sections and house elevations in areas threatened by the mountain flood disasters, determining disaster-forming water levels and corresponding flood peak flow frequency, calculating disaster-forming actual flood control capacity by combining with the relation of water level flow of control sections, counting the number of the hidden danger points and current situation flood control capacity by taking the villages and the towns as units, and calculating the danger degrees of different villages and towns according to a formula (1). In the ArcGIS system, after the results are subjected to normalized calculation, the mountain torrent disaster risk degree is divided into 4 grades of a low risk area, a medium risk area, a high risk area and a high risk area based on a natural breakpoint method.
Secondly, vulnerability analysis based on the village and town unit; when the hidden danger points of the mountain torrent disasters are investigated, the population, the family property and the residential housing types of the dangerous area are investigated and counted, and the population density and the economic density index of the dangerous area are calculated. According to the investigation result of the house structure of the dangerous area, the loss resistance of different house types is calculated by using a formula (2), and the loss resistance of the dangerous area house in units of villages and towns is obtained by using a formula (3). In the ArcGIS system, a population density and economic density of a dangerous area and a house damage resistance capability map layer which take a village and town unit as a plaque are established, the vulnerability based on the village and town unit is obtained through the calculation of a formula (4) through the spatial superposition analysis and the map layer calculation, and the result is subjected to normalized calculation.
Thirdly, risk zoning based on village and town units: in the ArcGIS system, a risk degree layer and a vulnerability layer are superposed, according to a formula (5), layer space superposition analysis and layer calculation are utilized to obtain a risk degree value of a village and town unit, and the risk degree is divided into a micro-degree risk area, a low-degree risk area, a medium-degree risk area, a high-degree risk area and a high-degree risk area through cluster analysis and a natural breakpoint classification method.
Further, the risk analysis based on the village and town unit in the first step includes:
in the investigation and evaluation process of the mountain torrent disaster hidden danger points, the flood forming water level and the corresponding flood peak flow frequency are determined by measuring the river section and the house elevation of the area threatened by the mountain torrent disaster, and the mountain torrent disaster frequency of the disaster-receiving body is calculated by combining the relation of the water level and the flow of the control section, namely the current situation flood control capacity. Taking villages and towns as units, counting the number of hidden danger points and the current flood control capacity, and calculating the danger of the mountain torrent disaster through the following formula:
in the formula, HiRepresenting the danger of mountain torrent disasters of villages and towns i, wherein the value of i is 1-n; p is a radical ofkCorresponding current flood control capacity for each hidden trouble point; n is a radical ofikThe number of hidden danger points with flood control capability of k in the current situation of a village and a town i is 20%, 10%, 5%, 2% and 1%, which respectively represent that the frequency of mountain torrent disasters is less than or equal to 5 years of meeting, 6-10 years of meeting, 11-20 years of meeting, 21-50 years of meeting and more than 50 years of meeting.
Further, after the result is subjected to normalized calculation, dividing the mountain torrent disaster risk into 4 grades of a low risk area, a medium risk area, a high risk area and a high risk area based on a natural breakpoint method; the method comprises the following steps of (1) bringing towns and towns which are distributed without hidden danger points into a low-risk area management category; the danger level of villages and towns with the number of potential hazard points of 5 years and below accounting for more than 50% is improved by level 1; adding a very high risk area on the basis of the original 4 risk area grades to obtain 5 risk grades, and obtaining mountain torrent disaster risk subareas based on village and town management and control units through grading.
Further, the vulnerability analysis based on the village and town unit in the second step includes:
vulnerability, namely loss possibly caused by disaster-bearing bodies when the disaster-bearing bodies are suffered from the disaster, calculating the vulnerability of the mountain torrent disaster based on the dangerous area statistical information in the investigation and evaluation results of the mountain torrent disaster and comprehensively considering population density, economic conditions and house structures; when the hidden danger points of the mountain torrent disaster are examined in detail, a dangerous area is defined aiming at the area threatened by the mountain torrent disaster, and special investigation and statistics are carried out on the population, the family property and the type of resident houses in the dangerous area; and calculating population density, economic density and house damage resistance of the danger area based on the survey evaluation result.
The damage of houses caused by mountain torrents can directly threaten the life and property safety of people, and is one of the important factors causing direct loss. The evaluation of house vulnerability is an important link for performing mountain torrent disaster risk assessment and planning and considering disaster prevention and reduction, and the damage resistance C of the mountain torrent disaster of the j-th house is determinedjThe calculation is as follows:
in the formula, TjThe j-th house damage-resistant coefficient is used for representing the capability of the house for resisting mountain torrent disasters; mj、MtThe number of the j-th type houses and the total number of the houses in a certain danger area are respectively.
The ability of a house to withstand mountain torrents is mainly related to the structure of the house and building material factors. According to the building structure, the number of building layers and the construction cost of the house, the types of houses in the dangerous area are roughly divided into four types by combining the investigation result: the brick-concrete three-layer brick-concrete two-layer brick-concrete one-layer brick-wood 2; the brick-concrete structure refers to that the main bearing components are constructed by reinforced concrete and bricks and woods, and the brick-wood structure refers to that the main weighing components are constructed by bricks or woods. According to different building structures and structure types, the damage capability of the mountain torrent disasters to houses is expressed as follows: the brick-wood structure is larger than the brick-concrete structure; one-storey houses > two-storey houses > three-storey houses; the two kinds of buildings are combined with the corresponding building cost to obtain the damage resistance coefficients of various buildings.
All indexes are calculated in the village and town units and used for providing a mountain torrent disaster risk grade division basis of the village and town units. Mountain torrent disaster house anti-damage energy C of villages and towns iiThe calculation is as follows:
in the formula, TjThe damage-resistant coefficient of the j-th house mountain torrent disasters; m is a group ofijIs a danger area of villages and towns iNumber of houses of inner j-th category.
Further, the method comprehensively considers the exposure of disaster-bearing bodies including population and economy, combines the loss resistance of houses, normalizes population density, economic property density and house disaster resistance in a dangerous area based on the population, family economy and house types in a village and town unit statistics according to the principle that people are more and more expensive than money, and evaluates the loss caused by the mountain torrent disaster by using the following formula:
v ═ 0.55P +0.45E) × (1-C) (formula 4)
In the formula, V is the vulnerability of the disaster bearing body; p is a risk area population normalization index; e is an economic normalization index of the danger area; and C is the damage resistance of the house in the danger area.
Further, the village-to-town unit-based risk zoning in step three comprises:
and (4) calculating the mountain torrent disaster risk degree of each village and town by using a formula (5) based on the estimation results of the mountain torrent disaster risk degree and the vulnerability. According to the risk degree, dividing the area into 5 types of mountain torrent disaster risk areas according to a naming mode: a microdegree risk zone, a low risk zone, a medium risk zone, a high risk zone, and a very high risk zone.
R ═ H × V (formula 5)
Wherein R is the risk; h is the risk; v is vulnerability.
Another object of the present invention is to provide a torrential flood disaster risk area and prediction system to which the torrential flood disaster risk area and prediction method described above are applied, the torrential flood disaster risk area and prediction system including:
the risk analysis module is used for carrying out risk analysis based on the village and town units;
the vulnerability analysis module is used for carrying out vulnerability analysis based on the village and town unit;
and the risk zoning module is used for carrying out risk zoning based on the village and town units.
Another object of the present invention is to provide a computer device including a memory and a processor, wherein the memory stores a computer program, and the computer program, when executed by the processor, causes the processor to execute the method for disaster risk zoning and prediction of torrential floods.
Another object of the present invention is to provide a computer-readable storage medium storing a computer program, which, when executed by a processor, causes the processor to execute the method for planning and predicting a risk of torrential flood disasters.
Another object of the present invention is to provide an information data processing terminal for implementing the mountain torrent disaster risk zoning and prediction system.
By combining all the technical schemes, the invention has the advantages and positive effects that: the mountain torrent disaster risk zoning and forecasting method provided by the invention comprehensively considers the disaster bearing body current situation flood control capability of factors such as drainage basin production convergence, river cross section and disaster water level, and can be used for representing the disaster occurrence risk. And selecting the population density, the family property density and the disaster resistance capability of the residential housing type in the mountain torrent disaster dangerous area according to the calculated indexes of the mountain torrent disaster vulnerability, and further calculating to obtain the mountain torrent disaster vulnerability in the Chongqing city.
In the invention, the flood-bearing embodiment flood control capability comprehensively considers factors of river basin production convergence, river cross section and disaster water level, and can reflect the danger of disaster relatively truly. Meanwhile, the villages and towns smaller than the counties are used as the computing unit, so that the actual mountain torrent disaster risk level in a small range can be more clearly disclosed and cannot be covered by a large-area trend, and a more effective mountain torrent disaster prevention plan can be guided to be made by local villages and towns according to the actual risk condition.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the embodiments of the present invention will be briefly described below, and it is obvious that the drawings described below are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained according to the drawings without creative efforts.
Fig. 1 is a flowchart of a mountain torrent disaster risk zoning and predicting method according to an embodiment of the present invention.
Fig. 2 is a block diagram of a mountain torrent disaster risk zoning and predicting system according to an embodiment of the present invention;
in the figure: 1. a risk analysis module; 2. a vulnerability analysis module; 3. a risk zoning module.
Fig. 3 is a schematic diagram of the distribution of the disaster risk levels of torrential floods in the Chongqing city according to an embodiment of the present invention.
Fig. 4 is a map of vulnerability to mountain torrent disasters in Chongqing cities based on village and town units provided by the embodiment of the invention.
Fig. 5 is a schematic view of risk levels of mountain torrent disasters in units of villages and towns in a Chongqing city according to an embodiment of the present invention.
Fig. 6 is a schematic view of the early-stage result of mountain torrent disaster risk degree in Chongqing city according to the embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is further described in detail with reference to the following embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
In view of the problems in the prior art, the present invention provides a method, a system, a device and a terminal for mountain torrent disaster risk zoning and prediction, and the present invention is described in detail below with reference to the accompanying drawings.
As shown in fig. 1, a method for partitioning and predicting risk of torrential flood disaster according to an embodiment of the present invention includes the following steps:
s101, risk analysis based on a village and town unit;
s102, vulnerability analysis based on a village and town unit;
and S103, carrying out risk zoning based on village and town units.
As shown in fig. 2, a mountain torrent disaster risk zoning and prediction system according to an embodiment of the present invention includes:
the risk analysis module 1 is used for carrying out risk analysis based on the village and town units;
the vulnerability analysis module 2 is used for carrying out vulnerability analysis based on the village and town unit;
and a risk zoning module 3 for performing risk zoning based on the village and town units.
The technical solution of the present invention is further described below with reference to specific examples.
The embodiment is as follows: chongqing city risk division based on village and town unit
1. The mountain torrent disaster early warning platform in Chongqing city generally extends to villages and towns, namely the villages and towns are basic units for carrying out mountain torrent disaster monitoring, early warning and emergency rescue and disaster relief, and for mountain torrent disaster defense work, a risk division taking the villages and the towns as units is easier to make and implement policies. Meanwhile, the mountain torrent disaster prevention and treatment work with villages and towns as units is basically developed around hidden danger points in the area, and when the mountain torrent disaster risk is analyzed, the mountain torrent disaster risk of the villages and the towns can be reflected according to the overall level of the hidden danger point risks.
The flood-fighting method comprehensively considers factors such as drainage basin production convergence, river cross section and disaster water level, and can be used for representing the risk of disaster. The index of the mountain torrent disaster vulnerability calculation selects the population density, the family property density and the ability of the residential housing type to resist disasters in the mountain torrent disaster dangerous area, and further calculates to obtain the mountain torrent disaster vulnerability of the Chongqing city (see table 1).
Table 1 mountain torrent disaster index system construction based on village and town units
2. Risk analysis based on village and town units
In the investigation and evaluation process of the mountain torrent disaster hidden danger points, river section and house elevation in the area threatened by the mountain torrent disaster are measured, disaster water level and corresponding flood peak flow frequency are determined, and the mountain torrent disaster frequency of a disaster-receiving body is calculated by combining the water level flow relation of the control section, which is also called current situation flood control capacity. The disaster-bearing embodiment flood control capability comprehensively considers factors such as drainage basin production convergence, river cross section, disaster water level and the like, and can reflect the danger of disaster occurrence more truly. And (3) counting the number of hidden danger points and the current flood control capacity by taking villages and towns as units, and calculating the risk of mountain torrent disasters according to the formula (1).
In the formula, HiRepresenting the danger of mountain torrent disasters of villages and towns i, wherein the value of i is 1-n; p is a radical ofkCorresponding current flood control capacity for each hidden trouble point; n is a radical ofikIn order to solve the problem that the flood control capability in the village and town i is k, k can be 20%, 10%, 5%, 2% and 1%, which respectively represent that the frequency of mountain torrent disasters is less than or equal to 5 years, 6-10 years, 11-20 years, 21-50 years and more than 50 years.
And after the results are subjected to normalized calculation, dividing the mountain torrent disaster risk degree of the Chongqing city into 4 grades of a low risk area, a medium risk area, a high risk area and a high risk area based on a natural breakpoint method. Wherein, the villages and towns without hidden danger point distribution are brought into the low-risk area management category. Meanwhile, considering the high risk of the area where the potential points are located in the first year and below, the risk level of the villages and towns with the number of the potential points in the first year and below of 5 years accounting for more than 50% is correspondingly improved by level 1. Therefore, a very high risk area is added on the basis of the original 4 risk area grades, and 5 risk grades are obtained. Accordingly, a mountain torrent disaster danger subarea in the Chongqing city based on the village and town control unit is divided (see fig. 3).
From the grading result of the dangerous area, generally, the dangers of flood disasters in the south-east and north-east of Yu are higher, and the overall dangers of the south-east and north-west of Yu are relatively lower. The risk level in the higher and higher regions is about 34.8% of the total area. The medium and low risk areas occupy 75.2% of the total area, are mainly located in places such as Yu main western regions, and are distributed in small quantities in other regions. The extremely high risk areas of mountain torrent disasters in Chongqing cities are distributed in Fengjie county, Wushan county, Wulong county, Xishan county and Yuyangyang county, and 8 towns are counted. 59 towns belonging to high risk areas are distributed in a plurality of counties sporadically, wherein the unitary county, Wulong county, Xiushan county, Wuxi county, Wushan county and Yunyang county are distributed more frequently. In addition, 188 villages and towns are divided into areas with higher risk of mountain torrent disasters. The method is roughly consistent with the consideration of rainfall conditions and the risk degree of multiple underlying surface factors in the early stage on the spatial distribution, and the potential of calculating mountain torrent disaster risk by the flood control capacity of the current situation of the hidden danger points is also shown.
3. Vulnerability analysis based on village and town unit
The vulnerability, namely the loss possibly caused by disaster recovery of disaster-bearing bodies, is calculated based on the statistical information of the dangerous areas in the investigation and evaluation result of the mountain torrent disasters and by comprehensively considering population density, economic conditions and house structures. When the hidden danger points of the mountain torrent disasters are examined in detail, a dangerous area is defined aiming at the area threatened by the mountain torrent disasters, and special investigation and statistics are carried out on the population, the family property and the types of the resident houses in the dangerous area. Through two-stage survey work, 21691 danger areas are planned in the whole city, and the total area is about 523.36km256 thousands of households, 198.90 thousands of people and 50.53 thousands of houses are involved. And calculating population density, economic density and house damage resistance of the danger area based on the survey evaluation result. The higher the population density and economic density, the higher the exposure, the greater the losses that may be incurred; and the stronger the damage-resistant ability of the house, the stronger the ability to resist mountain torrent disasters, and the less the loss is possibly suffered. In summary, in areas with relatively high vulnerability, large population density, high economic level, and limited ability of houses to resist mountain torrent disasters, huge life and property losses will be brought about once the mountain torrent disasters occur.
The damage of houses caused by mountain torrents can directly threaten the life and property safety of people, and is one of the important factors causing direct loss. Evaluating house vulnerability is an important link which needs to be considered for mountain torrent disaster risk assessment and disaster prevention and reduction planning. According to the related research results, the damage resistance (C) of the flood disaster of the j-th house can be determinedj) The calculation is as follows:
in the formula, TjThe j-th house damage-resisting coefficient is used for representing the capability of the house for resisting mountain torrent disasters; m is a group ofj、 MtThe number of the j-th type houses and the total number of the houses in a certain danger area are respectively.
The ability of a house to withstand mountain torrent disasters is mainly related to factors such as the structure of the house, building materials and the like. According to the building structure, the number of building layers and the construction cost of the house, the types of the house in the dangerous area of the Chongqing city can be roughly divided into four types by combining the investigation result: the brick-concrete three-layer brick-concrete two-layer brick-concrete one-layer brick-wood one-layer brick-concrete two-layer brick-concrete one-layer brick-wood one-layer brick-concrete two-layer brick-concrete one-layer brick-wood one-layer (1) and brick-wood one-layer (2). The brick-concrete structure refers to a main bearing member which is constructed by reinforced concrete and brick-wood. For example, the beam is made of reinforced concrete, and the bearing wall is a brick wall; or the beams are constructed of wood and the columns are reinforced concrete. The main components of the brick-wood structure, which are referred to as the weight, are constructed of bricks or wood. According to different building structures and structure types, the damage capability of the mountain torrent disaster to the house can be expressed as: the brick-wood structure is larger than the brick-concrete structure; one storey of residence is larger than two storeys of residence is larger than three storeys of residence. The two are combined with the corresponding house cost to obtain the loss resistance coefficients of various houses (see table 2).
TABLE 2 Damage resistance coefficient (T) of houses in mountain torrent disaster dangerous area in Chongqing City
The invention aims to provide a basis for dividing mountain torrent disaster risk levels of the village and town units, so that all indexes are calculated in the village and town units. Loss resistance of mountain torrent disaster house in villages and towns i (C)i) Can be calculated as:
in the formula, TjThe damage-resistant coefficient of the j-th house mountain torrent disasters; m is a group ofijThe number of the j-th type houses in the dangerous area of the village and the town i.
The method is characterized in that the method comprehensively considers the exposure of disaster-bearing bodies including population and economy, combines the loss resistance of houses, normalizes population density, economic property density and house disaster resistance in dangerous areas based on rural unit statistics, and evaluates the possible loss caused by the mountain torrent disaster by using a formula (4) according to the principle that people are more and more expensive than money.
V ═ 0.55P +0.45E) × (1-C) (formula 4)
In the formula, V is the vulnerability of the disaster bearing body; p is a risk area population normalization index; e is an economic normalization index of the danger area; and C is the damage resistance of the house in the danger area.
The calculation result shows that the vulnerability spatial distribution of the disaster-bearing body of the mountain torrent disaster in the Chongqing city shows obvious difference (see figure 4). On the whole, the vulnerability of the western area of Yu is the highest, and secondly, the middle area and northeast area of Yu are provided, and the southeast area of Yu is relatively lower. Wherein, villages and towns with higher vulnerability grade are concentrated in Yuxi areas such as Hechuan, Tong, Dazu, Jiangjin, Qijiang and Yubei; secondly, in the northeast Yuzhou areas such as the Wanzhou areas and the urban mouths; fengdu, Dingjiang and Wulong in Yu Zhong region, and Penshui, Xiushan and other counties in Yu southeast region. Compared with the previous research results based on counties, the vulnerability general trend is consistent, but there are more obvious differences in part of counties. For example: in the early result, the unitary sun is one of the areas with the highest vulnerability, but the vulnerability of the unitary sun is reduced according to the calculation mode of the dangerous area information division. Similarly, wuxi and wushan are less vulnerable than earlier results. And the vulnerability of Wulong, Fengdu and the prefecture and county such as Tenn is larger than that of the previous result. This is likely because, unlike earlier uses of the county unit's economy and population to characterize disaster-bearing entities, the present invention focuses on considering situations within the hazardous area. Theoretically, the adjustment can enable the calculation result to be closer to the real situation of the affected area of the mountain flood damage.
4. Risk zoning based on village and town units
And calculating the mountain torrent disaster risk degree of each village and town in Chongqing city by using a formula based on the estimation results of the mountain torrent disaster risk degree and the damage degree. According to the risk degree and the naming mode of earlier research, the Chongqing city is divided into 5 types of mountain torrent disaster risk areas: the results are shown in fig. 5 for the microdegree risk zone, the low risk zone, the medium risk zone, the high risk zone, and the very high risk zone.
It can be seen that the general spatial distribution of the mountain torrent disaster risk divisions obtained according to the present invention is similar to the previous results (fig. 6), and the areas with higher mountain torrent disaster risk in Chongqing city are mainly distributed in most of Yuxi areas and Yunortheast and Yusoutheast areas. Compared with earlier research results, areas and counties such as Yusoutheast Yuyang, Xiushan, Yuxintong, Dazu, Jiangjin, Qijiang and the like are consistently marked as mountain torrent disaster high-risk areas, but in the calculation result, the spatial positions of Yusoutheast and northeast mountain torrent disaster high-risk areas are different from those of earlier-stage analysis results, and especially Wushan, Wuxi and Wanzhou show approximately opposite mountain torrent disaster risk condition distribution. In the risk calculation taking villages and towns as units, the center of the high-incidence area of the Yu northeast disaster is in the Wanzhou area (the current flood control capacity is 69 percent of the total number of hidden trouble points in the area occupied by the hidden trouble points within 10 years), and the hidden trouble points are more distributed in the middle-altitude mountain area near the Yangtze river main stream, which is consistent with the existing research on the more frequent development of the mountain flood disaster at the middle-low altitude. The region is divided into middle and low risk regions in the risk degree region taking the county as the unit, and the middle risk high incidence region is distributed in high altitude mountain regions such as Kaizhou, City, Wuxi and Wushan. In addition, 260 hidden danger points are thoroughly searched in the Wulong area in the investigation and evaluation of the mountain torrent disasters, wherein the current flood control capacity of 53.46 percent of the hidden danger points is lower than that of one flood in 20 years. In the vulnerability calculation with counties as a unit, the Wulong district belongs to a region with low vulnerability, and when the calculation unit is refined to villages and towns, the vulnerability of most regions of the Wulong district is higher than the middle degree, which causes that in the risk calculation with counties as a unit, the Wulong district is divided into a low risk zone in the low-altitude mountainous region in the middle of Yu, and most villages and towns of the district are divided into a high risk zone in the middle of Yu and even an extremely high risk zone when villages and towns are used as units. Therefore, by adopting smaller towns than counties as the calculation unit, the actual risk level of the torrential flood disasters in a small range can be more clearly revealed, the risk level is not hidden by the trend of a large area, and the method is favorable for guiding local towns to make more effective torrential flood disaster prevention plans according to the actual risk conditions.
In the above embodiments, the implementation may be wholly or partially realized by software, hardware, firmware, or any combination thereof. When used in whole or in part, is implemented in a computer program product that includes one or more computer instructions. The procedures or functions described in accordance with the embodiments of the invention may be generated in whole or in part when the computer program instructions are loaded or executed on a computer. The computer may be a general purpose computer, a special purpose computer, a network of computers, or other programmable device. The computer instructions may be stored in a computer readable storage medium or transmitted from one computer readable storage medium to another, for example, the computer instructions may be transmitted from one website site, computer, server, or data center to another website site, computer, server, or data center via wire (e.g., coaxial cable, fiber optic, Digital Subscriber Line (DSL), or wireless (e.g., infrared, wireless, microwave, etc.)). The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device, such as a server, a data center, etc., that includes one or more of the available media. The usable medium may be a magnetic medium (e.g., floppy Disk, hard Disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., Solid State Disk (SSD)), among others.
The above description is only for the specific embodiments of the present invention, but the scope of the present invention is not limited thereto, and any modification, equivalent replacement, and improvement made by those skilled in the art within the technical scope of the present invention disclosed in the present invention should be covered within the scope of the present invention.
Claims (10)
1. A method for zoning and predicting mountain torrent disaster risk comprises the following steps:
firstly, risk analysis based on a village and town unit;
secondly, vulnerability analysis based on the village and town unit;
and step three, partitioning the risk based on the village and town units.
2. The mountain torrent disaster risk zoning and prediction method according to claim 1, wherein the risk analysis based on the village and town unit in the first step comprises: in the investigation and evaluation process of the mountain torrent disaster hidden danger points, the flood forming water level and the corresponding flood peak flow frequency are determined by measuring the river section and the house elevation of the area threatened by the mountain torrent disaster, and the mountain torrent disaster frequency of the disaster-receiving body is calculated by combining the water level flow relation of the control section, namely the current flood control capacity; taking villages and towns as units, counting the number of hidden danger points and the current flood control capacity, and calculating the risk of mountain torrent disasters according to the following formula:
in the formula, HiRepresenting the danger of mountain torrent disasters of villages and towns i, wherein the value of i is 1-n; p is a radical ofkCorresponding current flood control capacity for each hidden trouble point; n is a radical ofikThe number of hidden danger points with flood control capability of k in the current situation of a village and a town i is 20%, 10%, 5%, 2% and 1%, which respectively represent that the frequency of mountain torrent disasters is less than or equal to 5 years of meeting, 6-10 years of meeting, 11-20 years of meeting, 21-50 years of meeting and more than 50 years of meeting.
3. The method for mountain torrent disaster risk zoning and prediction according to claim 2, wherein after normalization calculation of the results, the mountain torrent disaster risk is divided into 4 levels of low risk zone, medium risk zone, high risk zone and high risk zone based on a natural breakpoint method; the method comprises the following steps of (1) bringing towns and towns which are distributed without hidden danger points into a low-risk area management category; the danger level of the villages and towns which meet or less than 5 years once is improved by 1 grade, wherein the number of the hidden danger points is more than 50%; adding a very high risk area on the basis of the original 4 risk area grades to obtain 5 risk grades, and dividing to obtain mountain torrent disaster risk subareas based on village and town management and control units.
4. The mountain torrent disaster risk zoning and prediction method according to claim 1, wherein the vulnerability analysis based on the village and town unit in the second step comprises: evaluating house vulnerability is an important link for mountain torrent disaster risk assessment and disaster prevention and reduction planning, and the damage resistance C of the mountain torrent disaster of the j-th house is measuredjThe calculation is as follows:
in the formula, TjThe j-th house damage-resistant coefficient is used for representing the capability of the house for resisting mountain torrent disasters; mj、MtThe number of j-th houses and the total number of houses in a certain dangerous area are respectively;
the capability of the house to resist mountain torrents is mainly related to the factors of the structure and the building materials of the house; according to the building structure, the number of building layers and the construction cost of a house, the types of the houses in the dangerous area are roughly divided into four types by combining the investigation result: the brick-concrete three-layer brick-concrete two-layer brick-concrete one-layer brick-wood 2; the brick-concrete structure refers to that main bearing components are built by reinforced concrete and bricks and woods, and the brick-wood structure refers to that main bearing components are built by bricks or woods; according to different building structures and structure types, the damage capability of the mountain torrent disasters to houses is expressed as follows: the brick-wood structure is larger than the brick-concrete structure; one-storey houses > two-storey houses > three-storey houses; the two are combined with the corresponding house cost to obtain the damage resistance coefficients of various houses;
all indexes are calculated in the village and town units and used for providing a mountain torrent disaster risk grade zoning basis of the village and town units; mountain torrent disaster house anti-damage energy C of villages and towns iiThe calculation is as follows:
in the formula, TjThe damage-resistant coefficient of the j-th house mountain torrent disasters; mijThe number of the j-th type houses in the dangerous area of the village and the town i.
5. The mountain torrent disaster risk zoning and forecasting method according to claim 4, wherein after normalization of population density, economic property density and house disaster resistance in the dangerous area based on the population, family economy and house type of the village and town unit statistics, the damage caused by the mountain torrent disaster is evaluated by using the following formula, taking comprehensive consideration of the exposure of disaster-bearing bodies including population and economy, and combining the damage resistance of houses:
V＝(0.55P+0.45E)×(1-C)
in the formula, V is the vulnerability of the disaster bearing body; p is a risk area population normalization index; e is an economic normalization index of the danger area; and C is the damage resistance of the house in the danger area.
6. The mountain torrent disaster risk zoning and prediction method according to claim 1, wherein the village and town unit based risk zoning in step three comprises: calculating to obtain the mountain torrent disaster risk degree of each village and each town by using a formula based on the estimation results of the mountain torrent disaster risk degree and the vulnerability; carrying out cluster analysis on the risk degree, and dividing the urban area into 5 types of mountain torrent disaster risk areas based on a natural discontinuous classification method: micro risk area, low risk area, medium risk area, high risk area and high risk area:
R＝H×V
wherein R is the risk; h is the risk; v is the vulnerability.
7. A torrential flood disaster risk zoning and prediction system for implementing the torrential flood disaster risk zoning and prediction method according to any one of claims 1 to 6, wherein the torrential flood disaster risk zoning and prediction system comprises:
the risk analysis module is used for carrying out risk analysis based on the village and town units;
the vulnerability analysis module is used for carrying out vulnerability analysis based on the village and town unit;
and the risk zoning module is used for carrying out risk zoning based on the village and town units.
8. A computer device comprising a memory and a processor, wherein the memory stores a computer program that, when executed by the processor, causes the processor to perform the method of mountain torrent disaster risk zoning and prediction according to any of claims 1-6.
9. A computer-readable storage medium storing a computer program which, when executed by a processor, causes the processor to execute the method for mountain torrent disaster risk zoning and prediction according to any one of claims 1 to 6.
10. An information data processing terminal for implementing the mountain torrent disaster risk zoning and prediction system according to claim 7.
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