Mountain torrent disaster risk assessment method for high-altitude mountain photovoltaic project

Abstract

The invention discloses a mountain torrent disaster risk assessment method for a high-altitude mountain photovoltaic project, and relates to the field of key infrastructure risk assessment. According to the method, representative indexes are selected from the three aspects of dangerousness, exposure degree and vulnerability, a mountain torrent disaster risk evaluation framework for the photovoltaic project is provided, a mountain torrent disaster risk evaluation index system is constructed according to the comprehensiveness, representativeness and the data availability principle, and compared with a current method, the index system is more comprehensive, more accurate and more reliable. Particularly, water factors, sand factors and the action relation between flood and sediment are comprehensively considered in various aspects of risk, exposure degree and vulnerability evaluation, and the sediment coupling problem is directly reflected by utilizing indexes such as the sediment content, the erosion and deposition change and the drainage basin solid source quantity in an index system; therefore, the method is particularly suitable for fine assessment of mountain torrent disaster risks caused by short-time heavy rainfall in a high-altitude mountain photovoltaic project.

Description

Technical Field

[0001] The present invention relates to the field of critical infrastructure risk assessment, and in particular to a method for assessing the risk of flash flood disasters in high-altitude mountain photovoltaic projects. Background Art

[0002] The statements in this section merely provide background information related to the present disclosure and may not constitute prior art.

[0003] Under the dual carbon goals of "carbon peak and carbon neutrality", photovoltaic power station projects have become an important clean energy infrastructure to cope with climate change. A large part of photovoltaic projects are built in high-altitude mountainous areas with abundant light resources. These areas (such as the mountainous areas in western my country) are often rugged in terrain, with thick surface weathering layers, frequent local rainstorms, steep floods, drastic adjustments in gully beds, and prominent disasters caused by coupled mountain floods and sand movement, which seriously threaten the safe operation of photovoltaic projects.

[0004] In order to ensure the safety of photovoltaic infrastructure in high-altitude mountains, it is urgent to carry out comprehensive assessment of flash flood risks at different stages of photovoltaic project planning, construction and operation and maintenance, and provide accurate information for dynamic assessment, early warning and prevention of flash flood disasters. Examples of mountainous areas with rainstorms and flash floods show that the coupling of sediment supply and floods is often a key factor in the occurrence of major flash flood disasters. Water and sediment disasters occur at the same time, and the two are intertwined. Sediment will not only change the water and sediment transport process, cause sudden changes in riverbed response and surges in flood levels, but may also cause secondary disasters such as weirs, debris flows and landslides. The coupling of water and sediment can easily lead to the phenomenon of "small water and big disasters".

[0005] The current risk assessment of flash flood disasters mainly considers rainstorm and flood disasters in mountainous areas. Based on regional meteorological conditions, hydrology and hydropower, topography and geomorphology and other factors, most of them follow the idea of ​​"rainstorm-flood-water level", focusing on the impact of "water" and ignoring the role of "sediment" in flash flood disasters. Therefore, it is impossible to comprehensively and objectively quantify the flash flood disaster risk of photovoltaic projects caused by short-term heavy rainfall. Summary of the invention

[0006] The purpose of the present invention is to solve the problems existing in the prior art, provide a flash flood disaster risk assessment method for high-altitude mountain photovoltaic projects, select representative indicators from three aspects of hazard, exposure and vulnerability, propose a flash flood disaster risk assessment framework for photovoltaic projects, and construct a flash flood disaster risk assessment index system based on the principles of comprehensiveness, representativeness and data availability. Compared with the current method, the index system is more comprehensive, especially in terms of hazard, exposure and vulnerability evaluation, comprehensively considering water factors and sand factors, as well as the relationship between floods and sediments, and using indicators such as sand content, scouring and silting changes, and solid material source quantity in the index system to directly respond to sediment coupling problems; therefore, this method is particularly suitable for the fine assessment of flash flood disaster risks caused by short-term heavy rainfall in high-altitude mountain photovoltaic projects.

[0007] The technical solution of the present invention is as follows:

[0008] A flash flood disaster risk assessment method for high-altitude mountain photovoltaic projects, including:

[0009] Step S1: construct a basic database based on multi-source data of photovoltaic projects;

[0010] Step S2: Constructing a flash flood risk assessment framework for PV projects;

[0011] Step S3: Based on the constructed photovoltaic project flash flood risk assessment framework, a photovoltaic project flash flood risk assessment index system is constructed from three levels: target layer, criterion layer, and indicator layer;

[0012] Step S4: Determine the weight of flash flood risk assessment index for photovoltaic projects;

[0013] Step S5: Based on the flash flood risk assessment index system for photovoltaic projects after weighting, comprehensive quantification and visualization of flash flood risks are achieved.

[0014] Furthermore, the step S1 comprises:

[0015] Through departmental surveys, field observations, questionnaires and drone remote sensing, we obtain meteorological and hydrological data, geographic information data, remote sensing image data, socio-economic data, photovoltaic project planning, construction and operation data, and build a basic database through ORACLE SPATIAL to facilitate classification management, quick query and real-time call of data information.

[0016] Furthermore, the step S2 comprises:

[0017] Combined with literature collection, summary and induction, we have a deep understanding of the concept of flash flood disasters, analyzed the disaster-causing mechanism of flash flood disasters on photovoltaic sites in plateau mountains, and defined the connotation and composition of flash flood risks of photovoltaic projects; starting from the two aspects of disaster-causing factors and disaster-bearing bodies, taking water and sand as the main interference factors, we constructed a flash flood risk assessment framework for photovoltaic projects based on hazard-exposure-vulnerability.

[0018] Furthermore, the step S3 comprises:

[0019] The flash flood disaster risk of photovoltaic projects is taken as the target layer, the flash flood hazard, exposure and vulnerability are taken as the criterion layer, and finally the specific indicators are taken as the indicator layer; according to the principles of constructing a flash flood disaster risk assessment index system for photovoltaic projects, the hazard index, exposure index and vulnerability index are selected respectively to construct a flash flood risk assessment index system for photovoltaic projects.

[0020] Furthermore, the selection of the risk index includes:

[0021] The hazard evaluation indicators were selected from the two dimensions of water factor and sand factor respectively; the three indicators of 6-hour rainfall, peak flow and peak water level were selected in terms of water factor; the three indicators of sediment content, erosion and deposition change and solid source in the basin were selected in terms of sand factor; the hazard indicators were then divided into five levels according to the degree of destructiveness: low hazard, low-medium hazard, medium hazard, medium-high hazard and high hazard, and the values ​​were assigned as 1, 2, 3, 4 and 5 respectively;

[0022] The exposure index selection includes:

[0023] In the physical subsystem, building area, road density, and equipment value are selected as representative indicators; in the social subsystem, personnel density is selected as the representative indicator; the exposure index is divided into 5 levels according to low exposure, low-medium exposure, medium exposure, medium-high exposure, and high exposure, and the values ​​are assigned as 1, 2, 3, 4, and 5 respectively;

[0024] The vulnerability indicators are selected as follows:

[0025] In terms of geographical and geological conditions, four indicators were selected, namely elevation, slope, soil moisture content and vegetation coverage rate. In terms of hydrological conditions, two indicators were selected, namely river channel mutation characteristics and river network density. In terms of adaptability, five indicators were selected, namely the age of personnel in the photovoltaic field, the educational level of personnel, the preparation of emergency plans, the degree of emergency drills, and emergency equipment and facilities. According to the degree of vulnerability, the vulnerability indicators were divided into five levels, namely low vulnerability, low-medium vulnerability, medium vulnerability, medium-high vulnerability and high vulnerability, and assigned values ​​of 1, 2, 3, 4 and 5 respectively.

[0026] Furthermore, the principles for constructing the flash flood disaster risk assessment index system for photovoltaic projects include: comprehensiveness, representativeness and data availability.

[0027] Furthermore, the step S4 comprises:

[0028] Step S41: using the analytic hierarchy process and the entropy method respectively to determine the weights of flash flood risk assessment indicators for photovoltaic projects;

[0029] Step S42: Based on the determination result of step S41, further determine the comprehensive weight of the flash flood risk assessment index of the photovoltaic project.

[0030] Furthermore, the step S1 comprises:

[0031] The weights of flash flood risk assessment indicators for photovoltaic projects are determined using the analytic hierarchy process, including:

[0032] First, we consulted experts from different departments in the form of questionnaires, compared the importance of each indicator, and constructed a judgment matrix through Yaahp software. The consistency of the judgment matrix was evaluated by calculating the consistency ratio CR. If CR < 0.1, it means that the judgment matrix is ​​reasonable. Further calculation is performed to obtain the weight of each indicator, which is marked as w 1_j , j represents an indicator;

[0033] The entropy method is used to determine the weights of flash flood risk assessment indicators for photovoltaic projects, including:

[0034] The entropy method is used to obtain the weight of the disaster resilience evaluation index of the photovoltaic project, marked as w 2_j The calculation formula is as follows:

[0035]

[0036] d j =1-H j

[0037]

[0038] Among them, H j is the entropy value of the jth indicator; f ij is the index proportion of the i-th evaluation object under the j-th evaluation index; X ij Assign the value of the i-th evaluation object under the j-th evaluation index; d j is the utility value of the jth indicator; w 2_j is the weight of the jth indicator calculated based on the entropy weight method.

[0039] Furthermore, the step S42 includes:

[0040] Based on the calculation results of the hierarchical analysis method and the entropy weight method, the average value is calculated to represent the comprehensive weight w of a certain indicator. j .

[0041] Furthermore, the step S5 comprises:

[0042] According to the results of indicator assignment and weight calculation, ArcGIS spatial overlay analysis was used to calculate the hazard H, exposure E and vulnerability V respectively. The calculation formula is as follows:

[0043] H=ΣW h_j X h_j , E=ΣW e_j X e_j , V=ΣW v_j X v_j

[0044] Where W h_j , W e_j , W v_j are the weights of the indicators of risk, exposure and vulnerability; X h_j , X e_j , X v_j They are the values ​​assigned to the indicators of hazard, exposure and vulnerability respectively;

[0045] According to the definition of risk, the higher the danger, exposure and vulnerability, the higher the risk level. According to the following relationship, the flash flood disaster risk of photovoltaic projects is comprehensively quantified with the help of ArcGIS raster computing function, and spatial visualization is achieved:

[0046] R=H×E×V

[0047] Based on the risk quantification results, the risk values ​​R in the range of 0≥R>1 are classified as low risk, those in the range of 1≥R>2 are classified as low-medium risk, those in the range of 2≥R>3 are classified as medium risk, those in the range of 3≥R>4 are classified as medium-high risk, and those in the range of 4≥R≥5 are classified as high risk. And spatial visualization expression is realized.

[0048] Compared with the prior art, the present invention has the following beneficial effects:

[0049] A flash flood disaster risk assessment method for high-altitude mountain photovoltaic projects solves the problem that the existing flash flood disaster risk assessment results are biased due to the general lack of consideration of sediment factors. This method specifically selects indicators such as sediment content, scouring and siltation changes, and solid material source quantity in the basin. It comprehensively considers water factors and sand factors, as well as the relationship between floods and sediments in all aspects of hazard, exposure and vulnerability evaluation. Therefore, the constructed flash flood disaster risk assessment index system is more comprehensive and objective than the current method, and is particularly suitable for the detailed assessment of flash flood disaster risks caused by short-term heavy rainfall in high-altitude mountain photovoltaic projects. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] Figure 1A flow chart of a flash flood disaster risk assessment method for a high-altitude mountain photovoltaic project;

[0051] Figure 2 This is a schematic diagram of an indicator system for risk assessment of flash flood disasters for photovoltaic projects in high-altitude mountains. DETAILED DESCRIPTION

[0052] It should be noted that relational terms such as "first" and "second" are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise a ..." do not exclude the existence of other identical elements in the process, method, article or device including the elements.

[0053] The features and performance of the present invention are further described in detail below in conjunction with the embodiments.

[0054] Embodiment 1

[0055] See also Figure 1-2 , a flash flood disaster risk assessment method for a high-altitude mountain photovoltaic project, specifically comprising the following steps:

[0056] Step S1: construct a basic database based on multi-source data of photovoltaic projects;

[0057] Step S2: Constructing a flash flood risk assessment framework for PV projects;

[0058] Step S3: Based on the constructed photovoltaic project flash flood risk assessment framework, a photovoltaic project flash flood risk assessment index system is constructed from three levels: target layer, criterion layer, and indicator layer;

[0059] Step S4: Determine the weight of flash flood risk assessment index for photovoltaic projects;

[0060] Step S5: Based on the flash flood risk assessment index system for photovoltaic projects after weighting, comprehensive quantification and visualization of flash flood risks are achieved.

[0061] In this embodiment, specifically, step S1 includes:

[0062] Through departmental surveys, field observations, questionnaire surveys, and drone remote sensing, we obtain multi-source data such as meteorological and hydrological data, geographic information data, remote sensing image data, socio-economic data, photovoltaic project planning, construction and operation data, and build a basic database through ORACLE SPATIAL to facilitate classification management, rapid query and real-time call of data;

[0063] That is, through the investigation of meteorological, hydrological and land departments, we can obtain social and economic data, meteorological and hydrological data, and geographical information data; through the on-site investigation and observation of photovoltaic projects, we can obtain the planning, construction and operation of photovoltaic projects, and obtain the aerial images of photovoltaic sites through UAV remote sensing. We can use ORACLE SPATIAL to build a basic database to realize the classification management, rapid query and real-time call of data.

[0064] In this embodiment, specifically, step S2 includes:

[0065] Combined with literature collection, summary and induction, we have a deep understanding of the concept of flash flood disasters, analyzed the disaster-causing mechanism of flash flood disasters on photovoltaic sites in plateau mountains, and defined the connotation and composition of flash flood risks of photovoltaic projects; starting from the two aspects of disaster-causing factors and disaster-bearing bodies, taking water and sand as the main interference factors, we constructed a flash flood risk assessment framework for photovoltaic projects based on "hazard-exposure-vulnerability".

[0066] In this embodiment, specifically, step S3 includes:

[0067] The flash flood disaster risk of photovoltaic projects is taken as the target layer, the flash flood hazard, exposure and vulnerability are taken as the criterion layer, and finally 21 specific indicators are taken as the indicator layer; according to the construction principles of the flash flood disaster risk assessment index system for photovoltaic projects, the hazard index, exposure index and vulnerability index are selected respectively (that is, based on literature research, the most widely used indicators for flash flood disaster risk assessment are summarized, taking into account both floods and sediments. According to the construction principles of the flash flood disaster risk assessment index system for photovoltaic projects shown in Table 1, indicators are selected from the three dimensions of hazard, sensitivity and adaptability to construct an evaluation index system), and the flash flood risk assessment index system for photovoltaic projects is constructed, as shown in Table 2.

[0068] Table 1 Principles for constructing a flash flood disaster risk assessment index system for photovoltaic projects

[0069]

[0070] Table 2: Risk assessment indicators for flash flood disasters in photovoltaic projects

[0071]

[0072]

[0073] In this embodiment, specifically, the selection of the risk index includes:

[0074] The hazard evaluation indicators were selected from the two dimensions of water factor and sand factor respectively; the three indicators of 6-hour rainfall, peak flow and peak water level were selected in terms of water factor; the three indicators of sediment content, erosion and deposition change and solid source in the basin were selected in terms of sand factor; the hazard indicators were then divided into five levels according to the degree of destructiveness: low hazard, low-medium hazard, medium hazard, medium-high hazard and high hazard, and the values ​​were assigned as 1, 2, 3, 4 and 5 respectively;

[0075] The exposure index selection includes:

[0076] From a system perspective, the photovoltaic project is summarized as a comprehensive disaster-prone body composed of a physical subsystem and a socio-economic subsystem. In the physical subsystem, building area, road density, and equipment value are selected as representative indicators. In the social subsystem, population density is selected as a representative indicator. The exposure index is divided into five levels: low exposure, low-medium exposure, medium exposure, medium-high exposure, and high exposure, and the values ​​are assigned as 1, 2, 3, 4, and 5 respectively.

[0077] The vulnerability indicators are selected as follows:

[0078] Vulnerability refers to the degree to which people, facilities and property in the evaluation area are susceptible to losses caused by natural disasters due to their own sensitivity and lack of ability to respond to adverse disturbances. The lower the vulnerability of the disaster-bearing body, the smaller the disaster risk, and vice versa. Therefore, first of all, in terms of geographical and geological conditions, four indicators are selected: elevation, slope, soil moisture content, and vegetation coverage. In terms of hydrological conditions, two indicators are selected: river channel mutation characteristics and river network density. In terms of adaptability, five indicators are selected: the age of personnel in the photovoltaic field, the education level of personnel, the preparation of emergency plans, the degree of emergency drills, and emergency equipment and facilities. According to the degree of vulnerability, the vulnerability indicators are divided into five levels: low vulnerability, low-medium vulnerability, medium vulnerability, medium-high vulnerability, and high vulnerability, and the values ​​are assigned to them as 1, 2, 3, 4, and 5 respectively.

[0079] That is, through literature research and expert consultation, the hazard index is divided into five levels according to the strength of destructiveness, namely low hazard, low-medium hazard, medium hazard, medium-high hazard and high hazard, and the values ​​are assigned to them respectively as 1, 2, 3, 4 and 5. Similarly, the exposure index is divided into five levels according to the degree of vulnerability, namely low exposure, low-medium exposure, medium exposure, medium-high exposure and high exposure, and the values ​​are assigned to them respectively as 1, 2, 3, 4 and 5. According to the degree of vulnerability, the vulnerability index is divided into five levels according to the degree of vulnerability, namely low vulnerability, low-medium vulnerability, medium vulnerability, medium-high vulnerability and high vulnerability, and the values ​​are assigned to them respectively as 1, 2, 3, 4 and 5.

[0080] In this embodiment, specifically, step S4 includes:

[0081] Step S41: using the analytic hierarchy process and the entropy method respectively to determine the weights of flash flood risk assessment indicators for photovoltaic projects; that is, to unify the assessment standards, it is necessary to clarify the relative weights of various indicators; in order to overcome the subjectivity of the expert scoring method and the shortcomings of the mathematical deduction method in describing the actual situation of the evaluation object, the present invention comprehensively uses the analytic hierarchy process and the entropy method to determine the weights of the flash flood risk indicators;

[0082] Step S42: Based on the determination result of step S41, further determine the comprehensive weight of the flash flood risk assessment index of the photovoltaic project.

[0083] In this embodiment, specifically, step S1 includes:

[0084] The weights of flash flood risk assessment indicators for photovoltaic projects are determined using the analytic hierarchy process, including:

[0085] First, we consulted experts from different departments in the form of questionnaires, compared the importance of each indicator, and constructed a judgment matrix through Yaahp software. The consistency of the judgment matrix was evaluated by calculating the consistency ratio CR. If CR < 0.1, it means that the judgment matrix is ​​reasonable. Further calculation is performed to obtain the weight of each indicator, which is marked as w 1_j , j represents a certain indicator; that is, a questionnaire is designed, and experts from different departments such as scientific research departments, water conservancy departments, meteorological departments, and photovoltaic project engineering are consulted to compare the importance of each indicator and obtain a judgment matrix; through Yaahp software, the relative importance of each indicator is defined as an exact integer between 1 and 9, and the sensitivity and consistency of the judgment matrix are evaluated by calculating the consistency ratio CR (CR<0.1 indicates that the judgment matrix is ​​reasonable). After passing the consistency test, the weight of each indicator is output through Yaahp software, marked as w 1_j ;

[0086] The entropy method is used to determine the weights of flash flood risk assessment indicators for photovoltaic projects, including:

[0087] The entropy method is used to obtain the weight of the disaster resilience evaluation index of the photovoltaic project, marked as w 2_j The calculation formula is as follows:

[0088]

[0089] d j =1-H j

[0090]

[0091] Among them, H j is the entropy value of the jth indicator; f ijis the index proportion of the i-th evaluation object under the j-th evaluation index; X ij Assign the value of the i-th evaluation object under the j-th evaluation index; d j is the utility value of the jth indicator; w 2_j is the weight of the jth indicator calculated based on the entropy weight method.

[0092] In this embodiment, specifically, step S42 includes:

[0093] Based on the calculation results of the hierarchical analysis method and the entropy weight method, the average value is calculated to represent the comprehensive weight w of a certain indicator. j ; That is, the average value of the indicator weights obtained by the hierarchical analysis method and the entropy value method represents the final weight of the flash flood disaster risk index, marked as w j ; The formula is as follows:

[0094] w j =(w 1_j +w 2_j )2

[0095] In this embodiment, specifically, step S5 includes:

[0096] According to the results of indicator assignment and weight calculation, ArcGIS spatial overlay analysis was used to calculate the hazard H, exposure E and vulnerability V respectively. The calculation formula is as follows:

[0097] H=∑W h_j X h_j , E=ΣW e_j X e_j , V = ∑ W v_j X v_j

[0098] Where W h_j , W e_j , W v_j are the weights of the indicators of risk, exposure and vulnerability; X h_j , X e_j , X v_j They are the values ​​assigned to the indicators of hazard, exposure and vulnerability respectively;

[0099] According to the definition of risk, the higher the hazard, exposure and vulnerability, the higher the risk level. According to the following relationship, with the help of ArcGIS raster calculation function and spatial overlay analysis module, the hazard, exposure and vulnerability evaluation results are spatially superimposed to comprehensively measure the flash flood disaster risk of photovoltaic projects and realize spatial visualization expression:

[0100] R=H×E×V

[0101] Based on the risk quantification results, the risk values ​​R in the range of 0 ≥ R > 1 are classified as low risk, those in the range of 1 ≥ R > 2 are classified as low-medium risk, those in the range of 2 ≥ R > 3 are classified as medium risk, those in the range of 3 ≥ R > 4 are classified as medium-high risk, and those in the range of 4 ≥ R ≥ 5 are classified as high risk. And realize spatial visualization and mapping; that is, based on the risk quantification results, according to the standards in Table 3, the flash flood disaster risks of photovoltaic projects are divided into five levels of low risk, low-medium risk, medium risk, medium-high risk and high risk according to the absolute value of risk, and realize spatial visualization and mapping.

[0102] Table 3. Risk classification standards for flash flood disasters in photovoltaic projects

[0103] Serial number Value at Risk (R) Risk Level 1 0≥R＞1 Low risk 2 1≥R＞2 Low-medium risk 3 2≥R＞3 Medium risk 4 3≥R＞4 Medium to high risk 5 4≥R≥5 High risk

[0104] The above-mentioned embodiments only express the specific implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the protection scope of the present application. It should be pointed out that, for ordinary technicians in this field, several variations and improvements can be made without departing from the technical solution concept of the present application, and these all belong to the protection scope of the present application.

[0105] This background section is provided to generally present the context of the invention, and the work of the presently named inventors, the work to the extent described in this background section, and aspects of this section that did not constitute prior art at the time of application are neither explicitly nor implicitly admitted to be prior art to the present invention.

Claims

1. A flash flood disaster risk assessment method for a high-altitude mountain photovoltaic project, characterized in that: include: Step S1: construct a basic database based on multi-source data of photovoltaic projects; Step S2: Constructing a flash flood risk assessment framework for PV projects; Step S3: Based on the constructed photovoltaic project flash flood risk assessment framework, a photovoltaic project flash flood risk assessment index system is constructed from three levels: target layer, criterion layer, and indicator layer; Step S4: Determine the weight of flash flood risk assessment index for photovoltaic projects; Step S5: Based on the flash flood risk assessment index system for photovoltaic projects after weighting, comprehensive quantification and visualization of flash flood risks are achieved.

2. According to claim 1, a method for assessing the risk of flash flood disasters in a high-altitude mountain photovoltaic project is characterized in that: The step S1 comprises: Through departmental surveys, field observations, questionnaires and drone remote sensing, we obtain meteorological and hydrological data, geographic information data, remote sensing image data, socio-economic data, photovoltaic project planning, construction and operation data, and build a basic database through ORACLE SPATIAL to facilitate classification management, quick query and real-time call of data information.

3. The method for assessing the risk of flash flood disasters in a high-altitude mountain photovoltaic project according to claim 2, characterized in that: The step S2 comprises: Combined with literature collection, summary and induction, we have a deep understanding of the concept of flash flood disasters, analyzed the disaster-causing mechanism of flash flood disasters on photovoltaic sites in plateau mountains, and defined the connotation and composition of flash flood risks of photovoltaic projects; starting from the two aspects of disaster-causing factors and disaster-bearing bodies, taking water and sand as the main interference factors, we constructed a flash flood risk assessment framework for photovoltaic projects based on hazard-exposure-vulnerability.

4. The method for assessing the risk of flash flood disasters in a high-altitude mountain photovoltaic project according to claim 3 is characterized in that: The step S3 comprises: The flash flood disaster risk of photovoltaic projects is taken as the target layer, the flash flood hazard, exposure and vulnerability are taken as the criterion layer, and finally the specific indicators are taken as the indicator layer; according to the principles of constructing a flash flood disaster risk assessment index system for photovoltaic projects, the hazard index, exposure index and vulnerability index are selected respectively to construct a flash flood risk assessment index system for photovoltaic projects.

5. The method for assessing the risk of flash flood disasters in a high-altitude mountain photovoltaic project according to claim 4, characterized in that: The selection of the indicators of the said risk includes: The hazard evaluation indicators were selected from the two dimensions of water factor and sand factor respectively; the three indicators of 6-hour rainfall, peak flow and peak water level were selected in terms of water factor; the three indicators of sediment content, erosion and deposition change and solid source in the basin were selected in terms of sand factor; the hazard indicators were then divided into five levels according to the degree of destructiveness: low hazard, low-medium hazard, medium hazard, medium-high hazard and high hazard, and the values ​​were assigned as 1, 2, 3, 4 and 5 respectively; The exposure index selection includes: In the physical subsystem, building area, road density, and equipment value are selected as representative indicators; in the social subsystem, personnel density is selected as the representative indicator; the exposure index is divided into 5 levels according to low exposure, low-medium exposure, medium exposure, medium-high exposure, and high exposure, and the values ​​are assigned as 1, 2, 3, 4, and 5 respectively; The vulnerability indicators are selected as follows: In terms of geographical and geological conditions, four indicators were selected, namely elevation, slope, soil moisture content and vegetation coverage rate. In terms of hydrological conditions, two indicators were selected, namely river channel mutation characteristics and river network density. In terms of adaptability, five indicators were selected, namely the age of personnel in the photovoltaic field, the educational level of personnel, the preparation of emergency plans, the degree of emergency drills, and emergency equipment and facilities. According to the degree of vulnerability, the vulnerability indicators were divided into five levels, namely low vulnerability, low-medium vulnerability, medium vulnerability, medium-high vulnerability and high vulnerability, and assigned values ​​of 1, 2, 3, 4 and 5 respectively.

6. The method for assessing the risk of flash flood disasters in a high-altitude mountain photovoltaic project according to claim 5, characterized in that: The principles for constructing the flash flood disaster risk assessment index system for photovoltaic projects include: comprehensiveness, representativeness and data availability.

7. A flash flood disaster risk assessment method for a high-altitude mountain photovoltaic project according to claim 6, characterized in that: The step S4 comprises: Step S41: using the analytic hierarchy process and the entropy method respectively to determine the weights of flash flood risk assessment indicators for photovoltaic projects; Step S42: Based on the determination result of step S41, further determine the comprehensive weight of the flash flood risk assessment index of the photovoltaic project.

8. The method for assessing the risk of flash flood disasters in a high-altitude mountain photovoltaic project according to claim 7, characterized in that: The step S1 comprises: The weights of flash flood risk assessment indicators for photovoltaic projects are determined using the analytic hierarchy process, including: First, we consulted experts from different departments in the form of questionnaires, compared the importance of each indicator, and constructed a judgment matrix through Yaahp software. The consistency of the judgment matrix was evaluated by calculating the consistency ratio CR. If CR < 0.1, it means that the judgment matrix is ​​reasonable. Further calculation is performed to obtain the weight of each indicator, which is marked as w 1_j , j represents an indicator; The entropy method is used to determine the weights of flash flood risk assessment indicators for photovoltaic projects, including: The entropy method is used to obtain the weight of the disaster resilience evaluation index of the photovoltaic project, marked as w 2_j The calculation formula is as follows: d j =1-H j Among them, H j is the entropy value of the jth indicator; f ij is the index proportion of the i-th evaluation object under the j-th evaluation index; X ij Assign the value of the i-th evaluation object under the j-th evaluation index; d j is the utility value of the jth indicator; w 2_j is the weight of the jth indicator calculated based on the entropy weight method.

9. A flash flood disaster risk assessment method for a high-altitude mountain photovoltaic project according to claim 8, characterized in that: The step S42 comprises: Based on the calculation results of the hierarchical analysis method and the entropy weight method, the average value is calculated to represent the comprehensive weight w of a certain indicator. j .

10. A flash flood disaster risk assessment method for a high-altitude mountain photovoltaic project according to claim 9, characterized in that: The step S5 comprises: According to the results of indicator assignment and weight calculation, ArcGIS spatial overlay analysis was used to calculate the hazard H, exposure E and vulnerability V respectively. The calculation formula is as follows: H=∑W h_j X h_j ,E=∑W e_j X e_j ,V=∑W v_j X v_j Where W h_j , W e_j , W v_j are the weights of the indicators of risk, exposure and vulnerability; X h_j , X e_j , X v_j They are the values ​​assigned to the indicators of hazard, exposure and vulnerability respectively; According to the definition of risk, the higher the danger, exposure and vulnerability, the higher the risk level. According to the following relationship, the flash flood disaster risk of photovoltaic projects is comprehensively quantified with the help of ArcGIS raster computing function, and spatial visualization is achieved: R=H×E×V Based on the risk quantification results, risk values ​​R in the range of 0≥R>1 are classified as low risk, those in the range of 1≥R>2 are classified as low-medium risk, those in the range of 2≥R>3 are classified as medium risk, those in the range of 3≥R>4 are classified as medium-high risk, and those in the range of 4≥R≥5 are classified as high risk, and spatial visualization expression is realized.

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