CN110298577B - Method and system for evaluating mountain torrent disaster risk along rivers and villages based on DPSIR model - Google Patents
Method and system for evaluating mountain torrent disaster risk along rivers and villages based on DPSIR model Download PDFInfo
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Abstract
The disclosure provides a method and a system for evaluating mountain torrent disaster risks in villages along rivers based on a DPSIR model. The evaluation method comprises the steps of selecting corresponding indexes of a driving force factor, a pressure factor, a state factor, an influence factor and a response factor, and constructing an index system based on a DPSIR model to form an index library; screening out a preset number of indexes related to each factor from an index library, acquiring corresponding index values and carrying out normalization processing; calculating the weight of the selected index; respectively multiplying the screened corresponding normalized index values of the pressure factors, the normalized index values of the state factors, the normalized index values of the influence factors and the normalized index values of the response factors by corresponding weights and then performing similar accumulation to obtain a pressure degree P, a bearing degree S, a vulnerability I and a stop loss R; and introducing the reduction bearing capacity and the reduction vulnerability, calculating to obtain comprehensive evaluation risk degree, and comparing with a preset risk grade threshold value to judge the mountain torrent disaster risk grade to which the river village belongs currently.
Description
Technical Field
The disclosure belongs to the field of disaster risk evaluation, and particularly relates to a method and a system for evaluating mountain torrent disaster risk in villages along rivers based on a DPSIR model.
Background
The statements in this section merely provide background information related to the present disclosure and may not necessarily constitute prior art.
The mountain torrent disaster refers to sudden flood caused by rainstorm, snow melting and the like in mountain areas, and has the characteristics of large water concentration flow rate, strong scouring destructive power, sand and even stones carried in water flow and the like, so that local flood is often caused. Due to the increasing range of human activities, mountain torrent disasters frequently occur in recent years. When a mountain torrent disaster occurs, firstly, the mountain torrent disaster is usually along rivers and villages which are close to river channels, the disaster resistance of village houses is poor, once the mountain torrent disaster occurs, the life and property safety of residents along the rivers can be seriously threatened, so the mountain torrent disaster prevention basic unit is along rivers and villages, and the evaluation of the mountain torrent disaster risk condition is increasingly important.
The Zhongcheng tiger and the like provide a flood risk zoning index model based on a geographic information system on the basis of analyzing each main factor of flood formation to obtain a flood risk comprehensive zone of the Liaohe river basin. Steve et al generalize mountain torrents into regional systems and begin analyzing mountain torrent disasters from both natural phenomena and social attributes. And adopting an Analytic Hierarchy Process (AHP) in Zhan Ministry and the like, and adopting a weighted average method to obtain the mountain torrent risk degree under the support of a GIS (geographic information System), thereby completing the flood risk evaluation of the three gorges reservoir area. According to the method, a GIS analysis tool is applied to Tangchuan and the like, a 1:25 geographic map is used as a basis, a dangerous area and a vulnerability map are subjected to superposition analysis, and a factor data layer inducing mountain torrent disaster formation and flooding is analyzed in a spatial integration manner. However, the characteristics of the mountain torrent disasters are diversified according to different index systems.
The inventor finds that the analysis and research on the mountain torrent disaster risk mostly uses a drainage basin or a county area as an analysis unit at present, most of selected indexes are regional indexes, the selected indexes are less developed along river villages, the mountain torrent disaster influence factors along the river villages are more, the related area is wider, a more appropriate index selection model is lacked, and the index selection is difficult to be sufficient and comprehensive; the risk evaluation indexes of mountain torrents in villages along rivers are more, the risk calculation is more complex, and the applicable evaluation indexes are less; therefore, the evaluation conclusion of the risk of the mountain torrent disaster at present is high in universality and representativeness, but is not sufficient in pertinence and applicability.
Disclosure of Invention
In order to solve the problems that mountain torrent disaster indexes along rivers are difficult to select, an index system is difficult to construct, and risk conditions are difficult to evaluate, a first aspect of the disclosure provides a mountain torrent disaster risk evaluation method along rivers and villages based on a DPSIR model.
In order to achieve the purpose, the following technical scheme is adopted in the disclosure:
a method for evaluating mountain torrent disaster risks along rivers in villages based on a DPSIR model comprises the following steps:
introducing the DPSIR model into the torrential flood disaster risk evaluation, defining driving force factors, pressure factors, state factors, influence factors and response factors in the model and endowing corresponding torrential flood disaster risk evaluation characteristics;
selecting corresponding sub-indexes of the driving force factor, the pressure factor, the state factor, the influence factor and the response factor, and constructing an index system based on a DPSIR model to form an index library;
screening out a preset number of indexes related to each factor from an index library, acquiring corresponding index values and carrying out normalization processing;
calculating the weight of the selected index by using an analytic hierarchy process;
the corresponding normalization index values of the screened pressure factors, the corresponding normalization index values of the state factors, the corresponding normalization index values of the influence factors and the corresponding normalization index values of the response factorsRespectively multiplying the obtained product by corresponding weight and then performing similar accumulation to obtain a pressure degree P, a bearing degree S, a vulnerability I and a loss stopping degree R; combining a DPSIR model relation diagram, considering the relation among factor indexes and the buffering reduction effect, and introducing the reduction pressure PReduction gearP × S and reduction vulnerability IReduction gearI × R; according to T ═ W1PReduction gear+W2IReduction gearCalculating to obtain a comprehensive risk degree T, wherein W1Is the weight value of the pressure factor, W2The weight value of the influence factor;
and comparing the comprehensive risk degree with a preset risk grade threshold value, and judging the mountain torrent disaster risk grade to which the river village belongs currently.
The method fully considers the relationship among the factor indexes and the buffer reduction effect, and resets the internal relationship of the DPSIR model; and performing risk analysis by combining factor values and comprehensive risk values of the five criterion layers, and performing comprehensive evaluation on mountain torrent disaster risks in villages along the river by combining risk grades.
A second aspect of the present disclosure provides a system for evaluating a disaster risk of torrential floods in villages along rivers based on a DPSIR model.
A along river village torrent disaster risk evaluation system based on DPSIR model includes:
the model fitting module is used for introducing the DPSIR model into the risk evaluation of the torrential flood disasters, defining driving force factors, pressure factors, state factors, influence factors and response factors in the model and endowing corresponding torrential flood disaster risk evaluation characteristics with the DPSIR model;
the index base building module is used for selecting corresponding indexes of the driving force factor, the pressure factor, the state factor, the influence factor and the response factor and building an index system based on a DPSIR model to form an index base;
the index value normalization module is used for screening out a preset number of indexes related to each factor from the index database, acquiring corresponding index values and carrying out normalization processing;
an index weight calculation module for calculating the weight of the selected index using an analytic hierarchy process;
degree of factorThe risk degree calculation module is used for multiplying the screened corresponding normalized index values of the pressure factors, the normalized index values of the state factors, the normalized index values of the influence factors and the normalized index values of the response factors by corresponding weights respectively and then performing similar accumulation to obtain a pressure degree P, a bearing degree S, a vulnerability I and a stop loss degree R; combining a DPSIR model relation diagram, considering the relation among factor indexes and the buffering reduction effect, and introducing the reduction pressure PReduction gearP × S and reduction vulnerability IReduction gearI × R; according to T ═ W1PReduction gear+W2IReduction gearCalculating to obtain a comprehensive risk degree T, wherein W1Is the weight value of the pressure factor, W2The weight value of the influence factor;
and the risk grade judging module is used for comparing the comprehensive risk degree with a preset risk grade threshold value and judging the mountain torrent disaster risk grade to which the river village belongs currently.
The method fully considers the relationship among the factor indexes and the buffer reduction effect, and resets the internal relationship of the DPSIR model; and performing risk analysis by combining factor values and comprehensive risk values of the five criterion layers, and performing comprehensive evaluation on mountain torrent disaster risks in villages along the river by combining risk grades.
A third aspect of the present disclosure provides a computer-readable storage medium.
A computer readable storage medium having stored thereon a computer program which, when being executed by a processor, implements the steps of the method for assessing along-river village torrent disaster risk based on a DPSIR model as described above.
A fourth aspect of the present disclosure provides a computer device.
A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor when executing the program implements the steps of the method for evaluating along-river village torrential flood disaster risk based on DPSIR model as described above.
The beneficial effects of this disclosure are:
(1) the DPSIR model is applied to the mountain torrent disaster risk evaluation, each index in the model is redefined, the internal relation of the model is reset, and the model is converted into a model system with the mountain torrent disaster risk evaluation characteristic.
(2) The method is based on the DPSIR model, a large number of indexes suitable for mountain torrent disaster risk evaluation are selected, and a mountain torrent disaster risk evaluation index database is constructed and used for selecting the evaluation indexes.
(3) According to the method, in the process of evaluating the risk of the river-following villages, the pressure degree, the bearing capacity, the vulnerability and the loss stopping degree are introduced, so that the method is used for evaluating the index conditions of all the criterions of mountain torrents disasters of the river-following villages, is beneficial to evaluating the defects in all aspects of flood control construction of the river-following villages, and accurately positions the weak points of flood control of the river-following villages.
(4) This disclosure is in terms of T ═ W1×P×S+W2And multiplying by R, calculating to obtain a comprehensive evaluation risk degree T, fully considering the relationship among the factors and the buffering reduction effect, calculating the comprehensive risk degree, and comprehensively evaluating the mountain torrent disaster risk in the villages along the river by combining the comprehensive risk degree.
Drawings
The accompanying drawings, which are included to provide a further understanding of the disclosure, illustrate embodiments of the disclosure and together with the description serve to explain the disclosure and are not to limit the disclosure.
Fig. 1 is a flowchart of a method for evaluating disaster risk of torrential floods in villages along rivers based on a DPSIR model according to an embodiment of the present disclosure.
Fig. 2 is a schematic structural diagram of a system for evaluating risk of mountain torrents along rivers in villages based on a DPSIR model according to an embodiment of the present disclosure.
Detailed Description
The present disclosure is further described with reference to the following drawings and examples.
It should be noted that the following detailed description is exemplary and is intended to provide further explanation of the disclosure. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this disclosure belongs.
It is noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of example embodiments according to the present disclosure. As used herein, the singular forms "a", "an" and "the" are intended to include the plural forms as well, and it should be understood that when the terms "comprises" and/or "comprising" are used in this specification, they specify the presence of stated features, steps, operations, devices, components, and/or combinations thereof, unless the context clearly indicates otherwise.
The DPSIR model is an evaluation index system conceptual model widely used in an environmental system, is developed as an index system for measuring environment and sustainable development, and considers the interaction between a human and the environmental system from the viewpoint of system analysis. It divides evaluation indexes characterizing a natural system into five types of Driving force (Driving forces), Pressure (Pressure), State (State), Impact (Impact) and response (Responses), and each type is divided into several indexes. The concept model of DPSIR is developed for comprehensive analysis and description of environmental problems and their relationship to social development, and is a common framework for organizing environmental status information. The framework originates from the research of sociology, and is applied to the environmental field and the sustainable development research as an organizational index system structure.
Example one
Fig. 1 is a flowchart of a method for evaluating disaster risk of torrential floods in villages along rivers based on a DPSIR model according to an embodiment of the present disclosure.
As shown in fig. 1, the method for evaluating a disaster risk of torrential floods in villages along rivers based on a DPSIR model of this embodiment includes:
s101: and redefining the DPSIR model and endowing the DPSIR model with the mountain torrent disaster characteristics.
And the internal relation of the model is reset, so that the relation is more reasonable and effective.
Selecting corresponding indexes of the driving force factor, the pressure factor, the state factor, the influence factor and the response factor, and constructing an index system based on a DPSIR model to form an index library.
Specifically, the driving force factor is a direct factor for promoting the development and change of the mountain torrent disasters; the driving force factor is the most original and most key index for prompting the occurrence of the mountain torrent disaster. For torrential flood disasters in villages and along rivers, the direct driving factor is mainly convergence generated by strong rainfall in a short time, so the related indexes of the driving force factors comprise: the characteristic time interval rainfall.
The pressure factor is pressure which is directly applied to the riverside villages after the action of driving force and promotes the development and the change of torrential flood disasters, and mainly refers to the state of the riverside villages under the action of terrain and river channel pressure; the related indexes of the pressure factors comprise topographic indexes, peak flood flows, river roughness and the like;
the state factor is the state of the river village under the action of pressure; the relevant indexes of the state factors comprise river bank conditions, distances between villages and rivers and the like;
the influence factor is the influence generated after the mountain torrent disaster, namely the vulnerability and vulnerability of the village; relevant indexes of the influence factors comprise the current village economic level, village population density, historical flood loss and the like;
the response factor is a countermeasure and a policy for mountain torrent disasters in villages along the river; the relevant indexes of the response factors comprise flood prevention system conditions, rescue goods and materials conditions, evacuation route conditions, resident disaster prevention consciousness conditions and the like.
When mountain torrent disasters occur along rivers and villages, driving force factors D brought by rainfall can play a promoting role in the mountain torrent disasters, and through factors such as influencing flood peak modulus, converging time and the like, pressure P is generated in flood control along the rivers and the villages. Due to the existence of pressure factors such as river channels and terrains, state S indexes such as dike construction along rivers and villages, distances between villages and rivers and the like are influenced, and meanwhile, I is influenced on economic level, population condition and the like of the villages. In order to eliminate the influence of the mountain torrent disaster, a certain response R is formed along the activities of human beings in villages of rivers, so the response R can counteract the influence I, change states S such as the state of a village embankment, the distance from the river and the like, and relieve the pressure P caused by the mountain torrent disaster.
Based on a DPSIR model, according to the scientific, objective, data availability and other index selection principles, 27 indexes capable of reflecting characteristics of river villages are selected in the embodiment, and a torrential flood disaster risk evaluation index system library is constructed. The index is selected as follows.
The driving force is a direct factor for promoting the development and the change of mountain torrent disasters, and mainly refers to a rainfall factor. The selectable indexes comprise:
(1) maximum 6h rainfall P6. The main cause of the mountain torrent disasters is short-duration strong rainfall, so that 6h of maximum rainfall is selected to evaluate the mountain torrent disasters in villages along rivers.
(2) Rainfall P within confluence timeSink (C). The confluence time along the village is the time that different points in the village region are converged on the cross section of the village, and the rainfall in the maximum confluence time for many years can represent the maximum rainfall experienced along the village and can further highlight the characteristics of all villages along the river.
(3) Maximum 24 hour rainfall P24. The index is not representative, but the data is easy to obtain. When rainfall data in villages along the river is deficient, the index can be selected temporarily.
The pressure is mainly a factor in small watershed and river channels. The selectable indexes comprise:
(1) integrated watershed gradient JDrainage basin. The comprehensive watershed gradient is the comprehensive gradient of the small watershed and can reflect the index of the convergence condition of the small watershed. The method has great influence on the generation and development of mountain torrent disasters in small flood areas. The indicator value may be extracted by a GIS tool.
(2) Elevation standard deviation HSign board. And reflecting the index of the dispersion degree of the elevation distribution of the small river basin. The index may be extracted by a GIS tool.
(3) Degree of relief GGet up. And the elevation difference between the highest point and the lowest point in the village area along the river reflects the fluctuation of the surface form.
(4) Comprehensive topographic index GHeald. The comprehensive indexes obtained by integrating the indexes such as terrain, gradient and elevation can fully reflect the terrain characteristics of the small watershed. The index may be extracted by a GIS tool.
(5) Convergence time TSink (C). The confluence time along the village of the river is the time for different points in the village area to converge on the cross section of the village, and reflects the confluence situation along the village of the river.
(6) Early stage affects rainfall Pa. The water content in the soil can influence the occurrence of mountain torrent disasters by influencing the convergence of small watershed production.
(7) Peak module Kp. The peak modulus refers to the peak flow Q of the control sectionFlood control systemThe ratio of the control area a. This index may reflect river characteristics. The calculation formula is as follows:
(8) comprehensive river course gradient JRiver course. The comprehensive river channel gradient is a weighted average of the ratio of the elevation difference between two adjacent points of the river channel to the horizontal distance between the two points, and can reflect the gradient of the river channel.
(9) Maximum flood velocity Vm. The ratio of the river channel flow Q to the cross-sectional area A. The calculation formula is as follows:
(10) peak flow QFlood control system. The peak flood flow is the maximum value to which the river flow increases when most of the high-strength runoff of the watershed is merged.
The state mainly refers to the state of villages along the river under the action of pressure. The index is difficult to quantify and can be scored according to actual conditions. The selectable indexes comprise:
(1) river course embankment situation S in village sectionEmbankment. The flood control capability of the dike is scored according to the integrity degree of the dike.
(2) Firmness of the house SHouse. And (4) scoring the firmness of the village house according to the house material and the quality in the village.
(3) Distance S between house and riverDistance between two adjacent plates. And calculating the proportion by combining the number of resident households in the village along the river and the total number of the residents in the village.
(4) Relative height H of house and river courseRelative to each other. Carrying out weighted average calculation by combining relative elevations of residents and river channels along the river of each household
The impact is mainly vulnerability and vulnerability along the river villages. The higher the vulnerability, the greater the loss after disaster in the village. The selectable indexes comprise:
(1) village status economic level EVillage. Village economic levels can be evaluated with human-average GDP.
(2) Village general population NVillage. The total number of people in villages.
(3) Village population density d. The ratio of the population P in a village to the area of the village. The calculation formula is as follows:
(4) infrastructure construction situation IConstruction of buildings. The actual conditions of whether large enterprises, schools and the like exist in the villages can be combined for scoring.
(5) Land utilization L. The method can be used for grading in combination with the value of the main planted crops in the village.
The response refers to countermeasures and policies taken for mountain torrent disasters along river villages. The index is difficult to quantify and can be scored according to actual conditions. Optional indicators thereof include;
(1) village flood control system condition RSystem of. The integral condition of the flood prevention system in the village and the personnel arrangement condition can be combined for scoring.
(2) Village flood prevention facility condition RFacility. The construction condition of flood prevention facilities in the village can be combined for scoring.
(3) Evacuation route situation RRoute. The scoring can be carried out by combining the number of evacuation routes in villages, road conditions and the like.
(4) Point of placement condition RMounting point. Scoring can be done in conjunction with the placement of the transfer points within the village.
(5) Disaster prevention consciousness R of residentsConsciousness of. The scoring can be carried out by combining the conditions of disaster prevention opening size, flood prevention drilling and the like in the village.
TABLE 1 index system table
S102: and screening out a preset number of indexes related to each factor from the index library, acquiring corresponding index values and carrying out normalization processing.
Specifically, obtaining a characteristic value of the selected index, and screening out indexes related to each factor by using a linear interpolation method to divide the indexes into n-level standards; obtaining the index value after index normalization by using the following formula:
wherein X' is an index actual value; h is an index assigned with a score value; s is an index standard value; x is a numerical value after index normalization, and subscript t represents the t-th criterion layer; the index j is an index value indicating the j-th index.
S103: and calculating the weight of the selected index by using an analytic hierarchy process.
Specifically, combining an analytic hierarchy process to construct a judgment matrix:
calculating the characteristic vector of the judgment matrix as each index weight: i λ E-Z | ═ 0.
aij denotes the number in the ith row and jth column, and belongs to the conventional expression of matrices, e.g. a32I.e. to the 3 rd row and 4 th column values. The main method for constructing the judgment matrix is to compare every two index elements in the index system by means of data search, expert consultation and the like, compare the relative importance of the elements, and use scale values to represent, and the scale is shown in table 2. And establishing a judgment matrix Z layer by layer in the hierarchical analysis model according to the sequence from top to bottom.
TABLE 2 Scale values table
S104: respectively multiplying the screened corresponding normalized index values of the pressure factors, the normalized index values of the state factors, the normalized index values of the influence factors and the normalized index values of the response factors by corresponding weights and then performing similar accumulation to obtain a pressure degree P, a bearing degree S, a vulnerability I and a stop loss R;
combining a DPSIR model relation diagram, considering the relation among factor indexes and the buffering reduction effect, and introducing the reduction pressure PReduction gearP × S and reduction vulnerability IReduction gearI × R; according to T ═ W1PReduction gear+W2IReduction gearCalculating to obtain a comprehensive evaluation risk degree T, wherein W1Is the weight value of the pressure factor, W2The weight value of the influence factor;
starting from five aspects of a driving force factor D, a pressure factor P, a state factor S, an influence factor I and a response factor R, introducing a risk degree and a pressure degree. The river-following village torrent disasters are classified and analyzed by 5 criterion layer factors of bearing strength, vulnerability and damage stopping degree, and weak links and weak points of the river-following village torrent disasters are accurately positioned, so that the evaluation content is more detailed and comprehensive, and the disaster prevention work is more accurate and effective. And respectively calculating the risk degree D, the pressure degree P, the bearing pressure degree S, the vulnerability I and the stop loss degree R according to a weighted comprehensive evaluation method. The specific formula is as follows:
the risk degree:
pressure degree:
bearing capacity:
vulnerability:
degree of damage prevention:
in the formula: wi、Wj、Wk、Wl、WmAre weight values of corresponding indexes; xi、Xj、Xk、Xl、XmIs the score of each index.
The driving force of the mountain torrent disasters in the villages along the river directly acts on the river channel and the underlying surface, and the mountain torrent disasters are influenced by the pressure formed by the converging mechanism of the river channel and the underlying surface, so that the comprehensive risk degree of the mountain torrent disasters in the villages along the river is influenced by the pressure index and is irrelevant to the driving force index.
When the pressure indexes change the state indexes of the riverside villages, the state indexes of the riverside villages can form a reaction, and the mountain torrent disaster pressure is reduced, so the bearing pressure can be used as a reduction coefficient of the bearing pressure, and the reduced bearing pressure can more accurately reflect the mountain torrent disaster pressure values born by the riverside villages. The reduction pressure calculation formula is as follows:
reducing the pressure bearing: pReduction gear＝P×S
Similarly, the influence I of the mountain torrent disaster prompts residents in villages along the river to make a response R, and meanwhile, the response can reduce the influence caused by the mountain torrent disaster. Therefore, the damage prevention degree can be regarded as reduction of the vulnerability, and the vulnerability after reduction can more accurately reflect the vulnerability degree of villages along the river. The reduction vulnerability calculation formula is as follows:
reducing vulnerability: i isReduction gear＝I×R
Therefore, the mountain torrent disaster risk degree in villages along rivers is mainly the result of combined action of reducing the pressure degree and reducing the vulnerability, and the pressure bearing degree and the vulnerability are respectively used as the reduction coefficients of the pressure degree and the vulnerability to participate in calculation.
In the embodiment, the pressure degree and the vulnerability are used as main factors influencing torrential flood disasters in river villages, the weight occupied by the pressure degree and the vulnerability in torrential flood disaster evaluation is respectively calculated, the buffering and reducing effects brought by the bearing pressure degree and the reducing degree in the river villages are comprehensively considered, and a new torrential flood disaster risk degree model is introduced: and (D, P, S, I and R), and calculating a comprehensive evaluation risk value by weighted reduction and superposition. The method comprises the following specific steps:
and (3) comprehensively evaluating the risk degree: t ═ W1×P×S+W2×I×R＝W1×PReduction gear+W2×IReduction gear；
In the formula: t is the comprehensive evaluation risk degree; w1Is the weight value of the pressure. W2Is the weight value occupied by the influence.
S105: and comparing the comprehensive risk degree with a preset risk grade threshold value, and judging the mountain torrent disaster risk grade to which the river village belongs currently.
The comprehensive evaluation risk degree is in the range of 0-1, and the risk grade is at least 3.
After the comprehensive evaluation risk degree is obtained, risk grade division is carried out according to the magnitude of the risk degree value and in combination with a risk grade division standard, so that the result is more visual and clear.
TABLE 2 hazard ratings
The Wendeng district Yingsi bridge small watershed and the Changyang river in the vegetable garden small watershed along the bank 5 villages are selected as research objects. The method is applied to the evaluation process by combining with a mountain torrent disaster risk evaluation method, the characteristics of small watershed and the characteristics of villages along rivers are fully considered, and the risk evaluation is carried out on the research object.
The mountain torrent disaster risk evaluation index system established in the embodiment is applied to mountain torrent disaster risk evaluation in villages along rivers in a research area, partial indexes are selected from the index library of the embodiment, and the mountain torrent disaster risk evaluation index system along the rivers is established, and detailed indexes of the mountain torrent disaster risk evaluation index system are shown in table 3.
TABLE 3 index system table
Weighting and superposing the normalized values of the indexes by using the weighted values calculated by the analytic hierarchy process and the normalized values of the index values in the evaluation system, and finally obtaining the factor degrees of each criterion layer of 5 river-along villages, wherein the obtained final result is shown in a table 4.
Table 4 risk profile index calculation results table
According to the index weight calculation method, the weights of the pressure and the influence factors are calculated, the obtained pressure degree, bearing capacity, vulnerability and loss stopping value are combined, the comprehensive evaluation risk degree formula of the embodiment is utilized, the comprehensive evaluation risk degree of the risk conditions of 5 river-along villages is finally calculated, and the final result is shown in table 5.
TABLE 5 comprehensive evaluation Risk calculation results Table
After the comprehensive evaluation risk degree is obtained, risk grade division is carried out according to the magnitude of the risk degree value and in combination with a risk grade division standard, so that the result is more visual and clear.
TABLE 6 comprehensive evaluation Risk calculation results Table
From the final results, the comprehensive evaluation risk value of mountain torrent disasters in the mountaineering and climbing villages is 0.386, so that the mountaineering and climbing villages have the highest risk. Analysis of the scores of the indexes shows that the danger degree D and the pressure degree P of the cross-country climbing are large, the comprehensive topographic index is large, the topography is steep, the confluence time is short, and houses in the cross-country climbing are old and have small flood resistance, so that the cross-country climbing village is required to strengthen flood prevention construction and focus flood prevention. The comprehensive evaluation risk value of the mountain torrent disasters in Zhao family, bed and villages is 0.29, and the risk is lowest. The analysis shows that the pressure value of Zhao family bed villages is lower, the topography is slower, the confluence time is long, and the influence of mountain torrents is less.
The embodiment combines the concrete current situation of along the river village, determines a series of reasonable indexes from 5 key factors of the mountain torrent disaster of the along the river village, combines a DPSIR model, formulates an index system according with the characteristics of the along the river village, and promotes the cognition and research process of the characteristics of the mountain torrent disaster of the along the river village. Finally, factor degrees and comprehensive evaluation risk degrees of all rule layers of the river-following villages are obtained, weak links and weak points of respective torrent disasters of each river-following village can be intuitively reflected, and key flood prevention and special regulation of the river-following villages are facilitated.
The DPSIR model is not universal in different fields, the content of the DPSIR model is redefined according to the torrential flood disaster risk evaluation requirement, and the internal relation of the model is reset, so that the DPSIR model can be suitable for torrential flood disaster risk evaluation.
The method is based on the DPSIR model, a large number of evaluation indexes of torrential flood disasters in the riverside villages are selected, an index library is constructed, and index selection can be provided for risk evaluation of torrential flood disasters in the riverside villages with different types and different characteristics.
In the process of risk assessment of the river-along villages, five criterion layer factor degree models of risk degree, pressure degree, bearing capacity, vulnerability and loss stopping degree are introduced for evaluating each criterion index condition of mountain torrent disasters of the river-along villages, so that the method is beneficial to evaluating the defects in all aspects of flood control construction of the river-along villages and accurately positioning the flood control weak points of the river-along villages.
In the final risk evaluation, the novel comprehensive risk model is introduced, the relation among the risk, the pressure, the bearing capacity, the vulnerability and the stopping loss degree and the buffering reduction effect are fully considered, and the obtained result is more comprehensive and accurate.
Example two
Fig. 2 is a schematic structural diagram of a system for evaluating risk of mountain torrents along rivers in villages based on a DPSIR model according to an embodiment of the present disclosure.
As shown in fig. 2, the present embodiment provides a system for evaluating disaster risk of torrential floods in villages along rivers based on a DPSIR model, including:
(1) the model fitting module is used for introducing the DPSIR model into the risk evaluation of the torrential flood disasters, defining driving force factors, pressure factors, state factors, influence factors and response factors in the model and endowing corresponding torrential flood disaster risk evaluation characteristics with the DPSIR model;
(2) the index base building module is used for selecting corresponding indexes of the driving force factor, the pressure factor, the state factor, the influence factor and the response factor and building an index system based on a DPSIR model to form an index base;
(3) the index value normalization module is used for screening out a preset number of indexes related to each factor from the index database, acquiring corresponding index values and carrying out normalization processing;
specifically, in the index value normalization module, an index related to each factor is screened out by using a linear interpolation method and divided into n-level standards; obtaining the index value after index normalization by using the following formula:
wherein X' is an index actual value; h is an index assigned with a score value; s is an index standard value; x is a numerical value after index normalization, and subscript t represents the t-th criterion layer; the index j is an index value indicating the j-th index.
(4) An index weight calculation module for calculating the weight of the selected index using an analytic hierarchy process;
(5) the factor degree and risk degree calculation module is used for multiplying the screened corresponding normalized index values of the pressure factors, the normalized index values of the state factors, the normalized index values of the influence factors and the normalized index values of the response factors by corresponding weights respectively and then performing similar accumulation to obtain a pressure degree P, a bearing degree S, a vulnerability I and a stop loss degree R; combining a DPSIR model relation diagram, considering the relation among factor indexes and the buffering reduction effect, and introducing the reduction pressure PReduction gearP × S and reduction vulnerability IReduction gearI × R; according to T ═ W1PReduction gear+W2IReduction gearCalculating to obtain a comprehensive risk degree T, wherein W1Is the weight value of the pressure factor, W2The weight value of the influence factor;
(6) and the risk grade judging module is used for comparing the comprehensive risk degree with a preset risk grade threshold value and judging the mountain torrent disaster risk grade to which the river village belongs currently.
Wherein the magnitude of the comprehensive evaluation risk degree is in the range of 0-1, and the risk grade is at least 3.
In this embodiment, the DPSIR model is applied to the risk evaluation of the torrential flood disaster, each index in the model is redefined, the internal relationship of the model is reset, and the model is converted into a model system having the risk evaluation characteristic of the torrential flood disaster.
In the embodiment, a large number of indexes suitable for mountain torrent disaster risk evaluation are selected based on a DPSIR model, and a mountain torrent disaster risk evaluation index database is constructed and used for selecting the evaluation indexes.
In the process of evaluating the risk of the river-along villages, the embodiment introduces the pressure degree, the bearing capacity, the vulnerability and the loss stopping degree, is used for evaluating the standard index conditions of mountain torrent disasters of the river-along villages, is favorable for evaluating the defects in all aspects of flood prevention construction of the river-along villages, and accurately positions the weak points of flood prevention of the river-along villages.
This embodiment is based on T ═ W1×P×S+W2And multiplying by R, calculating to obtain a comprehensive evaluation risk degree T, and calculating the comprehensive evaluation risk degree by fully considering the relationship among the factor degrees and the buffer reduction effect.
EXAMPLE III
The present embodiment provides a computer-readable storage medium, on which a computer program is stored, which when executed by a processor implements the steps in the method for assessing risk of torrential flood disasters in rivers and villages based on a DPSIR model as shown in fig. 1.
Example four
The embodiment provides a computer device, which comprises a memory, a processor and a computer program stored in the memory and capable of running on the processor, wherein the processor executes the program to realize the steps of the method for evaluating the risk of torrential flood disasters in villages and along rivers based on the DPSIR model shown in fig. 1.
As will be appreciated by one skilled in the art, embodiments of the present disclosure may be provided as a method, system, or computer program product. Accordingly, the present disclosure may take the form of a hardware embodiment, a software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present disclosure may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, optical storage, and the like) having computer-usable program code embodied therein.
The present disclosure is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the disclosure. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by a computer program, which can be stored in a computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. The storage medium may be a magnetic disk, an optical disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), or the like.
The above description is only a preferred embodiment of the present disclosure and is not intended to limit the present disclosure, and various modifications and changes may be made to the present disclosure by those skilled in the art. Any modification, equivalent replacement, improvement and the like made within the spirit and principle of the present disclosure should be included in the protection scope of the present disclosure.
Claims (8)
1. A method for evaluating mountain torrent disaster risks along rivers in villages based on a DPSIR model is characterized by comprising the following steps:
introducing the DPSIR model into the torrential flood disaster risk evaluation, defining driving force factors, pressure factors, state factors, influence factors and response factors in the model and endowing corresponding torrential flood disaster risk evaluation characteristics;
selecting corresponding sub-indexes of the driving force factor, the pressure factor, the state factor, the influence factor and the response factor, and constructing an index system based on a DPSIR model to form an index library;
the driving force factor is a direct factor for promoting the development and the change of the torrential flood disasters, the pressure factor is pressure which is directly applied to the torrential flood villages after the driving force acts and promotes the development and the change of the torrential flood disasters, the state factor is the state of the torrential flood villages under the action of the pressure, the influence factor is the influence generated after the torrential flood disasters, and the response factor is countermeasures and policies for the torrential flood disasters of the torrential flood villages;
the driving force factor related index includes a characteristic time period rainfall; the related indexes of the pressure factors comprise topographic indexes, peak flood flows and river roughness; the relevant indexes of the state factors comprise river bank conditions and distances between villages and rivers; relevant indexes of the influence factors comprise the current village economic level, the village population density and the historical flood loss; the relevant indexes of the response factors comprise flood prevention system conditions, rescue goods and materials conditions, evacuation route conditions and resident disaster prevention consciousness conditions;
screening out a preset number of indexes related to each factor from an index library, acquiring corresponding index values and carrying out normalization processing;
calculating the weight of the selected index by using an analytic hierarchy process;
respectively multiplying the screened corresponding normalized index values of the pressure factors, the normalized index values of the state factors, the normalized index values of the influence factors and the normalized index values of the response factors by corresponding weights and then performing similar accumulation to obtain a pressure degree P, a bearing degree S, a vulnerability I and a stop loss R; combining a DPSIR model relation diagram, considering the relation among factor indexes and the buffering reduction effect, and introducing the reduction pressure PReduction gearP × S and reduction vulnerability IReduction gearI × R; according to T ═ W1PReduction gear+W2IReduction gearCalculating to obtain a comprehensive risk degree T, wherein W1Is the weight value of the pressure factor, W2The weight value of the influence factor;
and comparing the comprehensive risk degree with a preset risk grade threshold value, and judging the mountain torrent disaster risk grade to which the river village belongs currently.
2. The method for evaluating torrent disaster risk along rivers and villages based on DPSIR model as claimed in claim 1, wherein linear interpolation is used to screen out indexes related to each factor and divide the indexes into n-level standards; obtaining the index value after index normalization by using the following formula:
wherein X' is an index actual value; h is an index assigned with a score value; s is an index standard value; x is a numerical value after index normalization, and subscript t represents the t-th criterion layer; the index j is an index value indicating the j-th index.
3. The method for evaluating the risk of mountain torrents along rivers and villages based on the DPSIR model as claimed in claim 1, wherein the magnitude of the comprehensive evaluation risk degree is in the range of 0-1, and the risk grade is at least 3.
4. The utility model provides a along river village torrent calamity risk evaluation system based on DPSIR model which characterized in that includes:
the model fitting module is used for introducing the DPSIR model into the risk evaluation of the torrential flood disasters, defining driving force factors, pressure factors, state factors, influence factors and response factors in the model and endowing corresponding torrential flood disaster risk evaluation characteristics with the DPSIR model;
specifically, the driving force factor is a direct factor for promoting the development and change of the mountain torrent disasters; the driving force factor is the most original and most key index for promoting the mountain torrent disasters, and for mountain torrent disasters in villages along rivers, the direct driving factor is mainly convergence generated by strong rainfall in a short time, so the related indexes of the driving force factor comprise: rainfall at characteristic time intervals;
the pressure factor is pressure which is directly applied to the riverside villages after the action of driving force and promotes the development and the change of torrential flood disasters, and mainly refers to the state of the riverside villages under the action of terrain and river channel pressure; the related indexes of the pressure factors comprise topographic indexes, peak flood flows, river roughness and the like;
the state factor is the state of the river village under the action of pressure; the relevant indexes of the state factors comprise river bank conditions, distances between villages and rivers and the like;
the influence factor is the influence generated after the mountain torrent disaster, namely the vulnerability and vulnerability of the village; relevant indexes of the influence factors comprise the current village economic level, village population density, historical flood loss and the like;
the response factor is a countermeasure and a policy for mountain torrent disasters in villages along the river; the relevant indexes of the response factors comprise flood prevention system conditions, rescue goods and materials conditions, evacuation route conditions, resident disaster prevention consciousness conditions and the like;
the index base building module is used for selecting corresponding indexes of the driving force factor, the pressure factor, the state factor, the influence factor and the response factor and building an index system based on a DPSIR model to form an index base;
the index value normalization module is used for screening out a preset number of indexes related to each factor from the index database, acquiring corresponding index values and carrying out normalization processing;
an index weight calculation module for calculating the weight of the selected index using an analytic hierarchy process;
the factor degree and risk degree calculation module is used for multiplying the screened corresponding normalized index values of the pressure factors, the normalized index values of the state factors, the normalized index values of the influence factors and the normalized index values of the response factors by corresponding weights respectively and then performing similar accumulation to obtain a pressure degree P, a bearing degree S, a vulnerability I and a stop loss degree R; combining a DPSIR model relation diagram, considering the relation among factor indexes and the buffering reduction effect, and introducing the reduction pressure PReduction gearP × S and reduction vulnerability IReduction gearI × R; according to T ═ W1PReduction gear+W2IReduction gearCalculating to obtain a comprehensive risk degree T, wherein W1Is the weight value of the pressure factor, W2The weight value of the influence factor;
and the risk grade judging module is used for comparing the comprehensive risk degree with a preset risk grade threshold value and judging the mountain torrent disaster risk grade to which the river village belongs currently.
5. The system for evaluating mountain torrent disaster risk along rivers and villages based on DPSIR model as claimed in claim 4, wherein in said index value normalization module, linear interpolation method is used to screen out indexes related to each factor and divide the indexes into n-level standards; obtaining the index value after index normalization by using the following formula:
wherein X' is an index actual value; h is an index assigned with a score value; s is an index standard value; x is a numerical value after index normalization, and subscript t represents the t-th criterion layer; the index j is an index value indicating the j-th index.
6. The system for evaluating mountain torrent disaster risk along rivers and villages based on DPSIR model as claimed in claim 4, wherein the magnitude of the comprehensive evaluation risk degree is in the range of 0-1, and the risk grade is at least 3.
7. A computer readable storage medium having stored thereon a computer program, which when executed by a processor performs the steps of the method for assessing risk of torrential flood disasters in river villages according to any of claims 1 to 3, based on the DPSIR model.
8. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor when executing the program implements the steps of the method for assessing torrential flood risk in rivers and villages based on DPSIR model as claimed in any one of claims 1 to 3.
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