Flood disaster prevention coping capacity evaluation method based on DPSIR framework

Abstract

The invention discloses a flood disaster prevention coping capacity evaluation method based on a DPSIR framework, and the method comprises the following steps: S1, building a flood disaster prevention coping capacity evaluation model based on the DPSIR framework, comprising a target layer, a criterion layer subordinate to the target layer, an element layer subordinate to the criterion layer and an index layer subordinate to the element layer in the flood disaster prevention coping capacity evaluation index system. S2, sequentially calculating index data in the index layer, indexes of elements in the element layer, indexes of criteria in the criterion layer and indexes of the target layer by adopting an analytic hierarchy process; and S3, grading the prevention coping capacity according to the target layer index through a quantile method, and completing flood disaster prevention coping capacity evaluation. The whole process of flood disaster prevention and coping is comprehensively considered, the flood disaster prevention and coping capacity is systematically and comprehensively evaluated from multiple angles and multiple levels, and the problems that an evaluation index system is not comprehensive, and targeted evaluation is not achieved are solved.

Description

Technical Field

[0001] The present invention belongs to the field of flood disaster prevention and response capability assessment, and specifically relates to a flood disaster prevention and response capability assessment method based on a DPSIR framework. Background Art

[0002] By conducting capacity assessment throughout the entire chain of flood disaster prevention and response, we can identify gaps and improve capabilities, which is of great significance for scientifically preventing and effectively responding to flood disasters and reducing casualties and property losses.

[0003] At present, there are few results related to the evaluation of flood disaster prevention and response capabilities. There are problems such as inappropriate evaluation model, incomplete evaluation index system, non-objective index weight setting, incomplete evaluation process, etc., which lead to qualitative evaluation, subjective evaluation, and non-targeted evaluation. DPSIR is a framework for organizing information and related indexes based on causal relationships. It describes the interaction between society and environment by establishing a causal relationship chain of driving force (Driving) - pressure (Pressure) - state (State) - impact (Impact) - response (Response), and has shown good applicability in social economy, natural resources, ecological environment, etc. The present invention provides a method for constructing flood disaster prevention and response capability evaluation based on the DPSIR framework, which solves the reality that there is a lack of quantitative evaluation methods for the entire chain of prevention and response capabilities. Summary of the invention

[0004] In view of the above-mentioned deficiencies in the prior art, the flood disaster prevention and response capability evaluation method based on the DPSIR framework provided by the present invention solves the problems of lack of flood disaster prevention and response capability evaluation method, insufficient quantitative evaluation and incomplete process coverage in the prior art.

[0005] In order to achieve the above-mentioned invention object, the technical solution adopted by the present invention is: a flood disaster prevention and response capability evaluation method based on the DPSIR framework, comprising the following steps: S1. Establish a flood disaster prevention and response capability evaluation model based on the DPSIR framework, including the target layer, the criterion layer under the target layer, the element layer under the criterion layer, and the indicator layer under the element layer in the flood disaster prevention and response capability evaluation index system; S2, using the analytic hierarchy process to calculate the index data of each indicator layer, the index of each factor in the factor layer, the index of each criterion in the criterion layer and the index of the target layer in sequence; S3. Use the quantile method to grade the prevention and response capabilities according to the target layer index to complete the evaluation of flood disaster prevention and response capabilities.

[0006] Further: in S1, the target layer is the flood disaster prevention and response capability, and the criteria in the criterion layer include driving force criteria, pressure criteria, state criteria, impact criteria and response criteria.

[0007] Further: the factors in the factor layer under the driving force criterion include natural factors and human factors; The index data in the index layer under natural factors include the average rainfall over many years, the distribution of flash flood disaster risk areas, the distribution of geological disaster hidden danger points and the distribution of flood-prone points; the index data in the index layer under human factors include the level of economic development, the contradiction between people and land and the status of engineering construction; The elements in the element layer under the stress criterion include natural stress, economic stress, and social stress; The indicator layer under natural pressure is specifically the frequency of rainstorms; the indicator data in the indicator layer under economic pressure include the damage to infrastructure, the interruption of industrial and agricultural production, the degree of deterioration of the investment environment and the degree of obstruction to economic development; the indicator data in the indicator layer under social pressure include the number of injuries, missing persons, deaths due to disasters, public health risk level and environmental damage risk level; The elements in the element layer under the status criteria include engineering protection measures and non-engineering protection measures; The indicator data in the indicator layer under engineering protection measures include the flood control construction compliance rate, drainage and flood control engineering system and mountain torrent diversion channel construction; the indicator data in the indicator layer under non-engineering protection measures include the construction of transfer and risk avoidance mechanism, monitoring and early warning coverage and the formulation of flood dispatch regulations; The elements in the element layer under the impact criteria include population vulnerability and property vulnerability; The indicator data in the indicator layer under population vulnerability include population density, number of risk population and number of special population; the indicator data in the indicator layer under property vulnerability include land property distribution and proportion of agricultural land; The elements in the element layer under the response criteria include the system, mechanism and law of the plan, measures in the prevention and preparation stage, measures in the emergency response stage and measures in the recovery and reconstruction stage; The indicator data in the indicator layer under the plan system, mechanism and law include the degree of perfection of the emergency plan, the establishment of disaster prevention agencies and departments, the mobilization mechanism of the rescue team, the degree of perfection of flood control laws and regulations, the establishment of the coordination and linkage mechanism and the establishment of the cross-regional joint prevention and control mechanism; the indicator data in the indicator layer under the prevention and preparation stage measures include the planning and construction budget, hidden danger investigation, risk assessment, information release method, number of training and drills, and team material construction and reserves; the indicator data in the indicator layer under the emergency response stage measures include the rescue force dispatch capability, social mobilization capability, medical treatment capability, factor guarantee capability and technical guarantee capability; the indicator data in the indicator layer under the recovery and reconstruction stage measures include the comprehensiveness of the disaster loss investigation, the depth of the review analysis and the rapidity of the reconstruction plan.

[0008] Further: S2 comprises the following sub-steps: S21. Collect the index data of each indicator layer in the flood disaster prevention and response capability evaluation model, and standardize the index data; S22, using the hierarchical analysis method to calculate the subjective weight of each indicator data in the indicator layer, using the entropy weight method to calculate the objective weight of the indicator data, calculating the distribution coefficient of the subjective weight and the objective weight, combining the subjective weight and the objective weight according to the distribution coefficient, and obtaining the weight of each indicator data; S23, based on the data and weights of each indicator in the indicator layer under each element, the index of each element in the element layer is calculated using the index analysis method; S24, based on the index and weight of each factor in the factor layer under the criterion, the index of each criterion in the criterion layer is calculated by using the index analysis method; S25. Based on the index and weight of each criterion in the criterion layer under the target layer, the target layer index is calculated using an index analysis method.

[0009] Further: In S21, the index data is standardized using the Z-Score method, and the standardized index data Y i The specific expression is:

[0010] In the formula, X i For the i The value of the indicator data, n The total number of indicator data.

[0011] Further: In said S22, i The weight of the indicator data W i The specific expression is:

[0012] In the formula, To calculate the distribution coefficient of subjective weight, To calculate the distribution coefficient of objective weight, For the i The subjective weight of the indicator data, For the i The objective weight of the indicator data.

[0013] Further: In S23, the index of any element in the element layer is calculated V The specific expression is:

[0014] In the formula, W i It is the index layer under the element. i The weight of the indicator, Y i It is the index layer under the element. i The standardized value of the indicator data.

[0015] Further: S3 is specifically: Based on the target layer index and quantile method to set the range of (0, 25%], (25%, 50%], (50%, 75%] and (75%, 100%]; When the target layer index is within the range of (0, 25%], the flood disaster prevention and response capacity is classified as a low level; When the target layer index is within the range of (25%, 50%), the flood disaster prevention and response capacity is classified as medium level; When the target layer index is within the range of (50%, 75%), the flood disaster prevention and response capacity is classified as a strong level; When the target layer index is within the range of (75%, 100%], the flood disaster prevention and response capabilities are classified as strong.

[0016] The beneficial effects of the present invention are: (1) The present invention provides a flood disaster prevention and response capability evaluation method based on the DPSIR framework, establishes a flood disaster prevention and response capability evaluation model based on the DPSIR framework, establishes an indicator system with driving force criterion, pressure criterion, state criterion, impact criterion and response criterion as the criterion layer, and decomposes the fundamental causes, direct causes, actual conditions, impacts and measures taken of flood disaster prevention and response into element layers, comprehensively considers the whole process of flood disaster prevention and response, and systematically and comprehensively evaluates flood disaster prevention and response capabilities from multiple angles and multiple levels, thus solving the problems of incomplete evaluation index system and non-targeted evaluation.

[0017] (2) The present invention establishes a flood disaster prevention and response capability evaluation model based on the DPSIR framework, and establishes a causal relationship chain for flood disaster prevention and response capability evaluation based on the DPSIR framework, in which the driving force criterion leads to the pressure criterion, the pressure criterion causes the state criterion to change, the state criterion change produces the influence criterion, and the influence criterion finally promotes the response criterion. At the same time, the response criterion will feedback the driving force criterion, the pressure criterion, the adjustment state criterion, and the compensation influence criterion, which are linked together and continuously change dynamically, thus establishing a dynamic reflection mechanism. Regularly conducting flood disaster prevention and response capability evaluation based on the DPSIR framework can intuitively reflect the status quo and development trend of various aspects of flood disaster prevention and response capability at a certain moment or a certain period, attract the attention of policy makers, and then find out the gaps and fill them, thus solving the problem of incomplete flood disaster prevention and response capability evaluation process and providing reference and support for the continuous improvement of prevention and response capability.

[0018] (3) According to the actual situation of flood disaster prevention and response, the present invention selects representative and operational evaluation indicators, constructs a flood disaster prevention and response capability evaluation index system based on the DPSIR framework, adopts hierarchical analysis method and entropy weight method to calculate the indicator weights, combines qualitative evaluation with quantitative evaluation, and is practical and operational. It solves the problems of subjective setting of flood disaster prevention and response capability evaluation indicator weights, as well as qualitative evaluation and subjective evaluation. It has practical significance for scientifically preventing and effectively responding to flood disasters and thus improving disaster prevention, mitigation and relief capabilities. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 This is a flow chart of the flood disaster prevention and response capability evaluation method based on the DPSIR framework of the present invention.

[0020] Figure 2 It is a schematic diagram of the DPSIR framework model of the present invention. DETAILED DESCRIPTION

[0021] The specific implementation modes of the present invention are described below so that those skilled in the art can understand the present invention. However, it should be clear that the present invention is not limited to the scope of the specific implementation modes. For those of ordinary skill in the art, as long as various changes are within the spirit and scope of the present invention as defined and determined by the attached claims, these changes are obvious, and all inventions and creations utilizing the concept of the present invention are protected.

[0022] like Figure 1 As shown, in one embodiment of the present invention, a flood disaster prevention and response capability evaluation method based on the DPSIR framework includes the following steps: S1. Establish a flood disaster prevention and response capability evaluation model based on the DPSIR framework, including the target layer, the criterion layer under the target layer, the element layer under the criterion layer, and the indicator layer under the element layer in the flood disaster prevention and response capability evaluation index system; S2, using the analytic hierarchy process to calculate the index data of each indicator layer, the index of each factor in the factor layer, the index of each criterion in the criterion layer and the index of the target layer in sequence; S3. Use the quantile method to grade the prevention and response capabilities according to the target layer index to complete the evaluation of flood disaster prevention and response capabilities.

[0023] In S1, the target layer is the flood disaster prevention and response capability, and the criteria in the criterion layer include driving force criteria, pressure criteria, state criteria, impact criteria and response criteria.

[0024] like Figure 2 As shown, in this embodiment, the flood disaster prevention and response capability evaluation model based on the DPSIR framework constructed by the present invention includes five criteria of driving force, pressure, state, impact and response, which are progressive in sequence to form a complete closed loop and causal chain.

[0025] The elements in the element layer under the driving force criterion include natural factors and human factors; The index data in the index layer under natural factors include the average rainfall over many years, the distribution of flash flood disaster risk areas, the distribution of geological disaster hidden danger points and the distribution of flood-prone points; the index data in the index layer under human factors include the level of economic development, the contradiction between people and land and the status of engineering construction; In this embodiment, the driving force criterion set by the present invention refers to the natural factors and human factors that promote the increase in flood disaster risks, resulting in casualties or property losses. The driving force criterion formed by potential natural factors and human factors puts pressure on flood disaster prevention and response, leading to pressure criteria, causing changes in the state of taking engineering and non-engineering measures, affecting the state criteria, and then affecting population vulnerability and property vulnerability, changing the impact criteria, and ultimately prompting the generation of a series of response measures to form a complete cause-and-effect chain.

[0026] The elements in the element layer under the stress criterion include natural stress, economic stress, and social stress; The indicator layer under natural pressure is specifically the frequency of rainstorms; the indicator data in the indicator layer under economic pressure include the damage to infrastructure, the interruption of industrial and agricultural production, the degree of deterioration of the investment environment and the degree of obstruction to economic development; the indicator data in the indicator layer under social pressure include the number of injuries, missing persons, deaths due to disasters, public health risk level and environmental damage risk level; In this embodiment, the pressure criterion set by the present invention refers to the pressure that causes changes in flood formation, evolution, disaster-causing, prevention, and response through the driving forces of natural and human factors, and the influence that promotes the development of prevention and response capabilities.

[0027] The elements in the element layer under the status criteria include engineering protection measures and non-engineering protection measures; The indicator data in the indicator layer under engineering protection measures include the flood control construction compliance rate, drainage and flood control engineering system and mountain torrent diversion channel construction; the indicator data in the indicator layer under non-engineering protection measures include the construction of transfer and risk avoidance mechanism, monitoring and early warning coverage and the formulation of flood dispatch regulations; In this embodiment, the state criterion set by the present invention refers to the actual situation of flood disaster prevention and response under the systematic influence of the driving force criterion-pressure criterion, and describes the state or trend of flood disaster prevention and response capabilities.

[0028] The elements in the element layer under the impact criteria include population vulnerability and property vulnerability; The indicator data in the indicator layer under population vulnerability include population density, number of risk population and number of special population; the indicator data in the indicator layer under property vulnerability include land property distribution and proportion of agricultural land; In this embodiment, the impact criterion set by the present invention refers to the final impact caused by changes in natural factors and human factors, that is, it is used to measure the changes in the state of flood disaster prevention and response capabilities caused by the action of pressure criteria and driving force criteria, representing observable positive or negative results.

[0029] The elements in the element layer under the response criteria include the system, mechanism and law of the plan, measures in the prevention and preparation stage, measures in the emergency response stage and measures in the recovery and reconstruction stage; The indicator data in the indicator layer under the plan system, mechanism and law include the degree of perfection of the emergency plan, the establishment of disaster prevention agencies and departments, the mobilization mechanism of the rescue team, the degree of perfection of flood control laws and regulations, the establishment of the coordination and linkage mechanism and the establishment of the cross-regional joint prevention and control mechanism; the indicator data in the indicator layer under the prevention and preparation stage measures include the planning and construction budget, hidden danger investigation, risk assessment, information release method, number of training and drills, and team material construction and reserves; the indicator data in the indicator layer under the emergency response stage measures include the rescue force dispatch capability, social mobilization capability, medical treatment capability, factor guarantee capability and technical guarantee capability; the indicator data in the indicator layer under the recovery and reconstruction stage measures include the comprehensiveness of the disaster loss investigation, the depth of the review analysis and the rapidity of the reconstruction plan.

[0030] In this embodiment, the response criteria set by the present invention refers to a series of positive measures formulated from the stages of plan system, mechanism and rule of law, as well as flood disaster prevention and preparation, emergency response, recovery and reconstruction, based on the driving force criterion-pressure criterion-state criterion-impact criterion system.

[0031] The S2 comprises the following sub-steps: The S2 comprises the following sub-steps: S21. Collect the index data of each indicator layer in the flood disaster prevention and response capability evaluation model, and standardize the index data; S22, using the hierarchical analysis method to calculate the subjective weight of each indicator data in the indicator layer, using the entropy weight method to calculate the objective weight of the indicator data, calculating the distribution coefficient of the subjective weight and the objective weight, combining the subjective weight and the objective weight according to the distribution coefficient, and obtaining the weight of each indicator data; S23, based on the data and weights of each indicator in the indicator layer under each element, the index of each element in the element layer is calculated using the index analysis method; S24, based on the index and weight of each factor in the factor layer under the criterion, the index of each criterion in the criterion layer is calculated by using the index analysis method; S25. Based on the index and weight of each criterion in the criterion layer under the target layer, the target layer index is calculated using an index analysis method.

[0032] In S21, the index data is standardized using the Z-Score method. Y i The specific expression is:

[0033] In the formula, X i For the i The value of the indicator data, n The total number of indicator data.

[0034] In this embodiment, the indicator data in the indicator layer set by the present invention includes natural attribute data and social attribute data, wherein the natural attribute data uses regular grids as evaluation units; the social attribute data uses villages or communities as evaluation units, and all indicator data are standardized using the Z-Score method to eliminate the influence of units and magnitudes.

[0035] In the S22, i The weight of the indicator data W i The specific expression is:

[0036] In the formula, To calculate the distribution coefficient of subjective weight, To calculate the distribution coefficient of objective weight, For the i The subjective weight of the indicator data, For the i The objective weight of the indicator data.

[0037] The specific expression for calculating the distribution coefficient of subjective weight and objective weight is:

[0038]

[0039] is the distribution coefficient of the calculated subjective weight, is the distribution coefficient of the calculated objective weight.

[0040] In S23, the index of any element in the element layer is calculated. V The specific expression is:

[0041] In the formula, W i It is the index layer under the element. i The weight of the indicator, Y i It is the index layer under the element. i The standardized value of the indicator data.

[0042] In this embodiment, the method for calculating the index of the target layer, the criterion layer and the element layer in the flood disaster prevention and response capability evaluation model based on the DPSIR framework is the same, and all of them are calculated by the index V The expression is calculated, so it is not described in detail.

[0043] The S3 is specifically: Based on the target layer index and quantile method to set the range of (0, 25%], (25%, 50%], (50%, 75%] and (75%, 100%]; When the target layer index is within the range of (0, 25%], the flood disaster prevention and response capacity is classified as a low level; When the target layer index is within the range of (25%, 50%), the flood disaster prevention and response capacity is classified as medium level; When the target layer index is within the range of (50%, 75%), the flood disaster prevention and response capacity is classified as a strong level; When the target layer index is within the range of (75%, 100%], the flood disaster prevention and response capabilities are classified as strong.

[0044] The beneficial effects of the present invention are as follows: the present invention provides a flood disaster prevention and response capability evaluation method based on the DPSIR framework, establishes a flood disaster prevention and response capability evaluation model based on the DPSIR framework, establishes an indicator system with driving force criteria, pressure criteria, state criteria, impact criteria and response criteria as criterion layers, and decomposes the fundamental inducements, direct causes, actual conditions, impacts and measures taken of flood disaster prevention and response item by item into element layers, comprehensively considers the whole process of flood disaster prevention and response, and systematically and comprehensively evaluates flood disaster prevention and response capabilities from multiple angles and multiple levels, thereby solving the problems of incomplete evaluation indicator system and non-targeted evaluation.

[0045] The present invention establishes a flood disaster prevention and response capability evaluation model based on the DPSIR framework, and establishes a flood disaster prevention and response capability evaluation causal relationship chain based on the DPSIR framework, wherein the driving force criterion leads to the pressure criterion, the pressure criterion causes the state criterion to change, the state criterion change produces the influence criterion, and the influence criterion finally promotes the response criterion to occur. At the same time, the response criterion will feedback the driving force criterion, the pressure criterion, the adjustment state criterion, and the compensation influence criterion, which are linked together and continuously change dynamically, thereby establishing a dynamic reflection mechanism. Regularly carrying out flood disaster prevention and response capability evaluation based on the DPSIR framework can intuitively reflect the status quo and development and change trends of various aspects of flood disaster prevention and response capabilities at a certain moment or a certain period, attract the attention of policy decision makers, and then find out the gaps and make up for the deficiencies, thereby solving the problem of incomplete flood disaster prevention and response capability evaluation process, and providing reference and support for the continuous improvement of prevention and response capabilities.

[0046] According to the actual situation of flood disaster prevention and response, the present invention selects representative and operable evaluation indicators, constructs a flood disaster prevention and response capability evaluation index system based on the DPSIR framework, adopts hierarchical analysis method and entropy weight method to calculate the indicator weights, combines qualitative evaluation with quantitative evaluation, has practicality and operability, solves the problems of objective setting of flood disaster prevention and response capability evaluation indicator weights, as well as qualitative evaluation and subjective evaluation, and has practical significance for scientifically preventing and effectively responding to flood disasters and thus improving disaster prevention, mitigation and relief capabilities.

[0047] In the description of the present invention, it is necessary to understand that the orientation or positional relationship indicated by the terms "center", "thickness", "upper", "lower", "horizontal", "top", "bottom", "inner", "outer", "radial", etc. is based on the orientation or positional relationship shown in the drawings, and is only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation on the present invention. In addition, the terms "first", "second", and "third" are used only for descriptive purposes, and cannot be understood as indicating or implying the relative importance or the number of implicitly specified technical features. Therefore, the features defined by "first", "second", and "third" may explicitly or implicitly include one or more of the features.

Claims

1. The flood disaster prevention and response capability evaluation method based on the DPSIR framework is characterized by: The following steps are involved: S1. Establish a flood disaster prevention and response capability evaluation model based on the DPSIR framework, including the target layer, the criterion layer under the target layer, the element layer under the criterion layer, and the indicator layer under the element layer in the flood disaster prevention and response capability evaluation index system; S2, using the analytic hierarchy process to calculate the index data of each indicator layer, the index of each factor in the factor layer, the index of each criterion in the criterion layer and the index of the target layer in sequence; S3. Use the quantile method to grade the prevention and response capabilities according to the target layer index to complete the evaluation of flood disaster prevention and response capabilities.

2. The flood disaster prevention and response capability evaluation method based on the DPSIR framework according to claim 1 is characterized in that: In S1, the target layer is the flood disaster prevention and response capability, and the criteria in the criterion layer include driving force criteria, pressure criteria, state criteria, impact criteria and response criteria.

3. The flood disaster prevention and response capability evaluation method based on the DPSIR framework according to claim 2 is characterized in that: The elements in the element layer under the driving force criterion include natural factors and human factors; The index data in the index layer under natural factors include the average rainfall over many years, the distribution of flash flood disaster risk areas, the distribution of geological disaster hidden danger points and the distribution of flood-prone points; the index data in the index layer under human factors include the level of economic development, the contradiction between people and land and the status of engineering construction; The elements in the element layer under the stress criterion include natural stress, economic stress, and social stress; The indicator layer under natural pressure is specifically the frequency of rainstorms; the indicator data in the indicator layer under economic pressure include the damage to infrastructure, the interruption of industrial and agricultural production, the degree of deterioration of the investment environment and the degree of obstruction to economic development; the indicator data in the indicator layer under social pressure include the number of injuries, missing persons, deaths due to disasters, public health risk level and environmental damage risk level; The elements in the element layer under the status criteria include engineering protection measures and non-engineering protection measures; The indicator data in the indicator layer under engineering protection measures include the flood control construction compliance rate, drainage and flood control engineering system and mountain torrent diversion channel construction; the indicator data in the indicator layer under non-engineering protection measures include the construction of transfer and risk avoidance mechanism, monitoring and early warning coverage and the formulation of flood dispatch regulations; The elements in the element layer under the impact criteria include population vulnerability and property vulnerability; The indicator data in the indicator layer under population vulnerability include population density, number of risk population and number of special population; the indicator data in the indicator layer under property vulnerability include land property distribution and proportion of agricultural land; The elements in the element layer under the response criteria include the system, mechanism and law of the plan, measures in the prevention and preparation stage, measures in the emergency response stage and measures in the recovery and reconstruction stage; The indicator data in the indicator layer under the plan system, mechanism and legal system include the degree of perfection of emergency plans, the establishment of disaster prevention agencies and departments, the rescue team mobilization mechanism, the degree of perfection of flood control laws and regulations, the establishment of coordination and linkage mechanisms, and the establishment of cross-regional joint prevention and control mechanisms; The indicator data in the indicator layer under the measures in the prevention and preparation stage include planning and construction budget, hidden danger inspection, risk assessment, information release method, number of training exercises, and team material construction and reserve; the indicator data in the indicator layer under the measures in the emergency response stage include rescue force dispatch capability, social mobilization capability, medical treatment capability, factor guarantee capability, and technical guarantee capability; the indicator data in the indicator layer under the measures in the recovery and reconstruction stage include the comprehensiveness of disaster loss investigation, the depth of review analysis, and the rapidity of reconstruction planning.

4. The flood disaster prevention and response capability evaluation method based on the DPSIR framework according to claim 1 is characterized in that: The S2 comprises the following sub-steps: S21. Collect the index data of each indicator layer in the flood disaster prevention and response capability evaluation model, and standardize the index data; S22, using the hierarchical analysis method to calculate the subjective weight of each indicator data in the indicator layer, using the entropy weight method to calculate the objective weight of the indicator data, calculating the distribution coefficient of the subjective weight and the objective weight, combining the subjective weight and the objective weight according to the distribution coefficient, and obtaining the weight of each indicator data; S23, based on the data and weights of each indicator in the indicator layer under each element, the index of each element in the element layer is calculated using the index analysis method; S24, based on the index and weight of each factor in the factor layer under the criterion, the index of each criterion in the criterion layer is calculated by using the index analysis method; S25. Based on the index and weight of each criterion in the criterion layer under the target layer, the target layer index is calculated using an index analysis method.

5. The flood disaster prevention and response capability evaluation method based on the DPSIR framework according to claim 4 is characterized in that: In S21, the index data is standardized using the Z-Score method. Y i The specific expression is: In the formula, X i For the i The value of the indicator data, n The total number of indicator data.

6. The flood disaster prevention and response capability evaluation method based on the DPSIR framework according to claim 5 is characterized in that: In the S22, i The weight of the indicator data W i The specific expression is: In the formula, To calculate the distribution coefficient of subjective weight, To calculate the distribution coefficient of objective weight, For the i The subjective weight of the indicator data, For the i The objective weight of the indicator data.

7. The flood disaster prevention and response capability evaluation method based on the DPSIR framework according to claim 5 is characterized in that: In S23, the index of any element in the element layer is calculated. V The specific expression is: In the formula, W i It is the index layer under the element. i The weight of the indicator, Y i It is the index layer under the element. i The standardized value of the indicator data.

8. The flood disaster prevention and response capability evaluation method based on the DPSIR framework according to claim 1 is characterized in that: The S3 is specifically: Based on the target layer index and quantile method to set the range of (0, 25%], (25%, 50%], (50%, 75%] and (75%, 100%]; When the target layer index is within the range of (0, 25%], the flood disaster prevention and response capacity is classified as a low level; When the target layer index is within the range of (25%, 50%), the flood disaster prevention and response capacity is classified as medium level; When the target layer index is within the range of (50%, 75%), the flood disaster prevention and response capacity is classified as a strong level; When the target layer index is within the range of (75%, 100%], the flood disaster prevention and response capabilities are classified as strong.

Images