A method for assessing the risk of forest fires in cold temperate zones

Abstract

The present invention belongs to the field of forest fire prevention, and in particular, relates to a method for assessing the fire hazard of cold temperate forests. The purpose of the present invention is to solve the problem of the lack of a suitable method for assessing the risk of forest fires in cold temperate forests. The intensity and type of forest fires are the main characteristics of forest fires, and can assess the degree of harm of fires to forest ecosystems, reflect the severity of forest burning, and determine the way to extinguish forest fires. Crown fires are not only strong in intensity, but also the most difficult to extinguish. Forest fires are the most dangerous and are the key forest fires to be prevented. According to the analysis and judgment of the potential intensity of forest fires and the types of forest fires that are prone to occur, the danger level is divided according to the destructiveness of forest fires and the difficulty of extinguishing. The subjectivity of assessing the risk of forest fires in the prior art is greatly reduced, and the problem of the lack of a scientific and reliable forest fire risk assessment method to guide forest fire prevention work in cold temperate forests in my country is solved.

Description

Technical Field

[0001] The invention belongs to the field of forest fire prevention, and in particular relates to a method for evaluating the fire hazard of cold-temperate forests. Background Art

[0002] Forest fire is a natural disaster that is sudden, destructive, and difficult to deal with and rescue. Forest fire risk assessment is to evaluate and estimate the possible forest fires and their intensity. Conducting forest fire risk assessment research helps to objectively understand the forest fire hazard level in different forest areas, so as to formulate corresponding fire prevention and fire fighting measures.

[0003] The occurrence and development of forest fires are affected by many factors, and there is a correlation between the influencing factors. It is very difficult to quantify the danger of forest fires. There are few studies on forest fire risk assessment in my country. In addition, the basic research on forest fires is weak. The existing fire hazard assessment methods mainly involve qualitative research by inviting experts to assign weights to various disaster factors (this method was adopted in the first national forest fire risk survey). This type of method relies on expert experience and is highly subjective. There are few risk assessment methods based on fire intensity. The assessment indicators of this method are not easy to obtain and are extremely difficult to operate in practice.

[0004] In summary, the existing technology lacks a suitable forest fire risk assessment method for cold-temperate forest areas and is unable to guide the practice of forest fire prevention work. Summary of the invention

[0005] The purpose of the present invention is to solve the problem that there is a lack of suitable forest fire risk assessment methods for cold temperate forests, which cannot guide the practice of forest fire prevention work. We propose a method for assessing the fire hazard of cold temperate forests.

[0006] S1: Obtain historical boreal forest data;

[0007] S2: preprocessing the historical cold temperate forest data obtained in S1 to obtain cold temperate forest fire risk assessment parameters;

[0008] S3: constructing a forest fire risk assessment model according to the cold temperate zone forest fire risk assessment parameters;

[0009] S4: Collect forest data for boreal forests to be assessed

[0010] S5: Inputting the collected cold-temperate forest data to be assessed into a cold-temperate forest fire hazard assessment model, and outputting a cold-temperate forest fire risk level.

[0011] The beneficial effects of the present invention are:

[0012] 1. The present invention aims at the fact that forest fire intensity and forest fire types are the main characteristics of forest fires. It can assess the degree of harm of fire to forest ecosystems, reflect the severity of forest burning, and determine the way to extinguish forest fires. Crown fires are not only intense but also the most difficult to extinguish. Forest fires are the most dangerous and are the key forest fires to be prevented. The potential intensity of forest fires and the types of forest fires that are prone to occur are determined by analysis and discrimination, and the danger levels are divided according to the destructiveness of forest fires and the difficulty of extinguishing them. This greatly reduces the subjectivity of forest fire risk assessment in the prior art, and solves the problem of strong subjectivity resulting in no forest fire risk assessment methods available in forest areas, and the inability to guide forest fire prevention work.

[0013] 2. The invention is highly operational. Only a ruler is needed for field investigation. No indoor test is required. The forest fire hazard level can be assessed on site, which is convenient for front-line personnel in forest areas to use. The operational difficulty is simplified and can guide forest fire prevention practices.

[0014] 3. This assessment method combines qualitative and quantitative methods and has a certain degree of flexibility. At the same time, according to the changes in forest flammability in different periods, it can realize dynamic assessment of forest fire hazards. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 The present invention discloses a forest fire hazard level map for standard sample plots in the Greater Khingan Range forest area of ​​Heilongjiang Province. DETAILED DESCRIPTION

[0016] Specific implementation method 1: Combination Figure 1 The invention is described, comprising:

[0017] S1: Obtain historical boreal forest data;

[0018] S2: preprocessing the historical cold temperate forest data obtained in S1 to obtain cold temperate forest fire risk assessment parameters;

[0019] S3: constructing a forest fire risk assessment model according to the cold temperate zone forest fire risk assessment parameters;

[0020] S4: Collect boreal forest data to be evaluated;

[0021] S5: Inputting the collected cold-temperate forest data to be assessed into a cold-temperate forest fire hazard assessment model, and outputting a cold-temperate forest fire risk level.

[0022] Specific implementation method 2: The difference between this implementation method and specific implementation method 1 is that:

[0023] The historical cold temperate forest data in S1 include: spring and autumn historical cold temperate forest data and summer historical cold temperate forest data, and non-seasonal historical cold temperate forest data;

[0024] The historical cold temperate forest data in spring and autumn include: the thickness of ground litter in spring and autumn X1, the density of shrubs in spring and autumn ρ1, the height of shrubs in spring and autumn h1, and the number of flammable tree species in one mu of sample plot in spring and autumn Y1;

[0025] The historical cold temperate forest data in summer include: summer ground litter thickness X2, summer shrub density ρ2, summer shrub height h2 and the number of flammable tree species in a 1-acre plot in summer Y2;

[0026] The non-seasonal historical cold temperate forest data include: average forest slope θ, initial windless spreading speed of litter R0, wind speed correction coefficient K w , combustible tree species litter load coefficient A and combustible tree species litter load thickness coefficient B, and surface litter calorific value H.

[0027] The present invention has strong operability. For field investigation of forest land, only a ruler is needed as a measuring tool. The determination and calculation methods are as follows:

[0028] A standard plot of 1 mu square (25.82m×25.82m) was laid out, and 4 sample plots (2m×2m) were set up 3m away from each corner vertex of the standard plot. The number of shrubs in all sample plots (including saplings with a diameter less than 5cm and height less than 30cm) was investigated, and the total number of shrubs divided by 16 was the shrub density. Three standard shrubs of average size (root diameter and height at the average level) were selected in the sample plot, and their heights were measured.

[0029] The number of flammable tree species in the survey plots (the main flammable tree species in the cold temperate forest zone are conifers, including Scots pine, larch, spruce, etc.). If it is a pure forest composed of flammable tree species, the number of all trees will be surveyed. The density of pure forests of non-flammable tree species is 0, and only the number of flammable tree species will be surveyed in mixed forests. Statistics were collected on the stand density of more than 3,000 coniferous forest survey plots in the area.

[0030] In actual assessment, it is only necessary to input the thickness of surface litter, forest slope, shrub density, shrub height, and density of flammable tree species into the system model, and the forest fire hazard level of the area can be assessed on site. The other steps and parameters are the same as the first specific implementation method.

[0031] Specific implementation method three: The difference between this implementation method and specific implementation method one is that in S2, the historical cold temperate forest data obtained in S1 is preprocessed to obtain the cold temperate forest fire risk assessment parameters; the specific process is:

[0032] S2.1: Obtain the spring and autumn cold temperate forest fire hazard assessment parameters based on the spring and autumn historical cold temperate forest data and the non-seasonal historical cold temperate forest data;

[0033] S2.2: Based on summer historical boreal forest data and non-seasonal historical boreal forest data, obtain summer boreal forest fire hazard assessment parameters.

[0034] This assessment method combines qualitative and quantitative methods and has a certain degree of flexibility. According to the changes in forest flammability in different periods, the combination of three indicators can be appropriately adjusted to achieve a dynamic assessment of forest fire hazard. The other steps are the same as those of specific implementation methods one to two.

[0035] Specific implementation method 4: This implementation method is different from specific implementation methods 1 to 4 in that:

[0036] In S2.1, the cold temperate forest fire risk assessment parameters in spring and autumn are obtained based on the historical cold temperate forest data in spring and autumn and the non-seasonal historical cold temperate forest data; the cold temperate forest fire risk assessment parameters in spring and autumn include: the initial fire intensity value I1 of the forest fire surface in spring and autumn, the continuous value L1 of the shrub layer in spring and autumn, and the density P1 of flammable tree species in spring and autumn; the specific process is:

[0037] S2.1.1: Calculate the initial fire intensity value I1 of forest fires on the ground in spring and autumn;

[0038] S2.1.2: Calculate the continuous value of the shrub layer L1 in spring and autumn;

[0039] S2.1.3: Calculate the density P1 of flammable tree species in spring and autumn;

[0040] In S2.2, the summer cold temperate forest fire risk assessment parameters are obtained based on the summer historical cold temperate forest data and the non-seasonal historical cold temperate forest data; the summer cold temperate forest fire risk assessment parameters include: summer forest fire surface initial fire intensity value I2, summer shrub layer continuous value L2, summer flammable tree species density P2, the specific process is:

[0041] S2.2.1: Calculate the initial fire intensity value I2 of the summer forest fire surface;

[0042] S2.2.2: Calculate the continuous value of the summer shrub layer, L2;

[0043] S2.2.3: Calculate the density P2 of tree species that are flammable in summer.

[0044] The intensity and type of forest fire are the main characteristics of forest fire behavior. They can assess the degree of harm of fire to forest ecosystems, reflect the severity of forest burning, and determine the way to extinguish forest fires. From the perspective of forest fire types, crown fires are the most intense and the most difficult to extinguish, and forest fires are the most dangerous. It is scientific and feasible to identify the potential intensity of forest fires and the types of forest fires that are prone to occur, and to divide the danger levels according to the destructiveness of forest fires and the difficulty of extinguishing them. The other steps and parameters are the same as those of the specific implementation methods one to three.

[0045] Specific implementation method 5: This implementation method is different from specific implementation methods 1 to 4 in that:

[0046] The specific process of calculating the initial fire intensity value of forest fire surface in spring and autumn in S2.1.1 is as follows:

[0047] I1=HW1R1 (1)

[0048] Where, I1 is the initial fire intensity of forest fires in spring and autumn; H is the calorific value of surface litter; W1 is the effective fuel load in spring and autumn; R1 is the initial forest fire spread speed in spring and autumn;

[0049] The calculation formula for the initial forest fire spread speed R1 in spring and autumn described in formula (1) is:

[0050]

[0051] In formula (2), R0 is the initial fire spread speed in horizontal windless conditions (m / min), K w is the wind speed correction factor, K S1 is the correction coefficient of fuel allocation pattern in spring and autumn, and θ is the average slope of the forest land;

[0052] The correction coefficient K of the combustible material configuration pattern in spring and autumn described in formula (2) S1 The calculation formula is:

[0053]

[0054] In formula (1), the calculation formula for the effective combustible load W1 in spring and autumn is:

[0055] W1=A+BX1 (4)

[0056] In the formula (4), A represents the litter load coefficient of combustible tree species, B represents the litter load thickness coefficient of combustible tree species, and X1 represents the thickness of the litter on the ground surface in spring and autumn;

[0057] Among them, the litter load coefficient for coniferous forests is A1=0.38, and the litter load thickness coefficient for coniferous forests is B1=0.97;

[0058] For the broad-leaved forest litter load coefficient A2 = 0.48, the broad-leaved forest litter load thickness coefficient B2 = 0.05;

[0059] For the litter load coefficient of combustible tree species in coniferous and broad-leaved mixed forests, A3 = 0.34, and the litter load thickness coefficient of coniferous and broad-leaved mixed forests, B3 = 0.12;

[0060] The calculation formula for the continuous value L1 of the shrub layer in spring and autumn in S2.1.2 is:

[0061] L1=ρ1×h1 (5)

[0062] In formula (5), ρ1 represents the density of shrubs in spring and autumn, h1 represents the height of shrubs in spring and autumn;

[0063] The calculation formula for the density P1 of flammable tree species in spring and autumn in S2.1.3 is:

[0064]

[0065] In formula (6), Y1 represents the number of flammable trees in one mu of sample land in spring and autumn. Other steps and parameters are the same as those in the first to fourth embodiments.

[0066] Specific implementation method 6: This implementation method is different from specific implementation methods 1 to 5 in that:

[0067] The specific process of calculating the initial fire intensity value of the summer forest fire surface in S2.2.1 is as follows:

[0068] I2=HW2R2 (7)

[0069] Where, I2 is the initial fire intensity of forest fire on the ground in summer; W2 is the effective fuel load in summer; R2 is the initial forest fire spread speed in summer;

[0070] The calculation formula for the initial forest fire spread speed R2 in summer described in formula (7) is:

[0071]

[0072] In formula (8), R0 is the initial fire spread speed in horizontal windless state (m / min), K w is the wind speed correction factor, K S2 is the correction coefficient of summer fuel configuration pattern, θ is the average slope of the forest land;

[0073] The correction coefficient K of the combustible material configuration pattern in summer described in formula (8) S2 The calculation formula is:

[0074]

[0075] In formula (7), the calculation formula for the effective combustible load W2 in summer is:

[0076] W2=A+BX2 (10)

[0077] In the formula (10), A represents the litter load coefficient of combustible tree species, B represents the litter load thickness coefficient of combustible tree species, and X2 represents the litter thickness on the ground in summer;

[0078] Among them, the litter load coefficient for coniferous forests is A1=0.38, and the litter load thickness coefficient for coniferous forests is B1=0.97;

[0079] For the broad-leaved forest litter load coefficient A2 = 0.48, the broad-leaved forest litter load thickness coefficient B2 = 0.05;

[0080] For the litter load coefficient A3 of the mixed coniferous and broadleaved forest = 0.34, and the litter load thickness coefficient B3 of the mixed coniferous and broadleaved forest = 0.12, the calculation formula for the continuous value L2 of the summer shrub layer in S2.2.2 is:

[0081] L2=ρ2×h2 (11)

[0082] In formula (11), ρ2 represents the summer shrub density, h2 represents the summer shrub height;

[0083] The calculation formula for the density P2 of flammable tree species in summer in S2.2.3 is:

[0084]

[0085] In formula (12), Y2 represents the number of flammable tree species in one mu of plot in summer.

[0086] The potential "initial fire intensity" can be used to estimate the possibility of forest fire occurrence and the development trend of forest fire. The potential "initial fire intensity" indicator can reflect the potential heat storage of combustible materials in the dead branches and leaves layer and the flammability of combustible materials.

[0087] The laboratory has measured the calorific value of litter on the ground of different forest types in the cold temperate forest zone of my country, see the table below:

[0088] Table 1 Calorific value of litter

[0089]

[0090] The spot burning experiment method was used to determine the initial windless spread speed of litter in different forest types in the cold temperate forest zone of my country, as shown in the following table:

[0091] Table 2 Horizontal windless initial fire spread speed

[0092]

[0093] The wind speed correction factor is shown in the following table:

[0094] Table 3 Wind speed correction coefficient table

[0095]

[0096] ; Other steps and parameters are the same as those in Specific Implementation Methods 1 to 5.

[0097] Specific implementation method 7: This implementation method is different from specific implementation methods 1 to 6 in that:

[0098] The forest fire risk assessment model in S3 includes a spring and autumn forest fire risk assessment model and a summer forest fire risk assessment model; the forest fire risk assessment model is constructed according to the cold temperate zone forest fire risk assessment parameters; the specific process is:

[0099] S3.1: Construct a spring and autumn forest fire risk assessment model based on the spring and autumn cold temperate forest fire risk assessment parameters;

[0100] S3.2: Construct a summer forest fire hazard assessment model based on the summer cold temperate zone forest fire hazard assessment parameters.

[0101] The other steps and parameters are the same as those in Specific Embodiments 1 to 6.

[0102] Specific implementation eight: This implementation differs from specific implementations one to seven in that:

[0103] In S3.1, a spring and autumn forest fire risk assessment model is constructed based on the spring and autumn cold temperate zone forest fire risk assessment parameters; the specific process is:

[0104] S3.1.1: The initial fire intensity value I1 of forest fires on the ground in spring and autumn obtained in S2.1 is processed by the tertile method to obtain the index value α1 of the litter layer on the ground in spring and autumn;

[0105] The continuous value L1 of the spring and autumn shrub layer obtained by S2.1 was processed using the tertile method to obtain the index value β1 of the spring and autumn shrub layer;

[0106] The density P1 of flammable tree species in spring and autumn obtained by S2.1 was processed using the tertile method to obtain the index value γ1 of the forest canopy in spring and autumn;

[0107] S3.1.2: Based on the spring and autumn surface litter layer index value α1 and the spring and autumn shrub layer index value β1, the initial surface fire risk level is determined to obtain the spring and autumn initial surface fire risk level;

[0108] S3.1.3: According to the spring and autumn forest canopy index value γ1, the initial surface fire risk level is corrected to obtain the spring and autumn fire hazard level;

[0109] In S3.2, a summer forest fire risk assessment model is constructed based on the summer cold temperate zone forest fire risk assessment parameters. The specific process is as follows:

[0110] S3.2.1: Use the tertile method to process the initial fire intensity value I2 of the summer forest fire surface obtained in S2.2 to obtain the summer surface litter layer index value α2;

[0111] The continuous value L2 of the summer shrub layer obtained by S2.2 was processed using the tertile method to obtain the summer shrub layer index value β2;

[0112] The density P2 of flammable tree species in summer obtained by S2.2 was processed using the tertile method to obtain the summer forest canopy index value γ2;

[0113] S3.2.2: Based on the summer surface litter layer index value α2 and the summer shrub layer index value β2, the initial surface fire risk level is determined to obtain the summer initial surface fire risk level;

[0114] S3.2.3: Based on the summer canopy index value γ2, the initial surface fire risk level is corrected to obtain the summer fire hazard level.

[0115] The other steps and parameters are the same as those in Specific Embodiments 1 to 7.

[0116] Specific implementation method 9: This implementation method is different from specific implementation methods 1 to 8 in that:

[0117] In S3.1.1, the ternary method is used to process the initial fire intensity value I1 of the forest fire surface in spring and autumn obtained in S2.1 to obtain the index value α1 of the litter layer on the surface in spring and autumn. The specific process is as follows:

[0118]

[0119] In formula (13), x 11 and x 12 is a percentage variable with a value range of (0,1), the percentage variable x 11 and x 12 The initial fire intensity value I1 of forest fires in spring and autumn obtained by S2.1 is processed by the tertile method to obtain the percentage value corresponding to the quantile, I 1max is the maximum initial fire intensity value of forest fires on the ground in spring and autumn obtained in S2.1;

[0120] The tertile method is used to process the spring and autumn shrub layer continuous value L1 obtained in S2.1 to obtain the spring and autumn shrub layer index value β1; the specific process is:

[0121]

[0122] In formula (14), y 11 and 12is a percentage variable with a value range of (0,1), the percentage variable y 11 and 12 is the quantile obtained by processing the continuous value L1 of the spring and autumn shrub layer obtained in S2.1 using the tertile method, and the corresponding percentage value, L 1max is the maximum continuous value of the spring and autumn shrub layer obtained by S2.1;

[0123] The ternary method is used to process the density P1 of flammable tree species in spring and autumn obtained in S2.1 to obtain the spring and autumn forest canopy index value γ1; the specific process is:

[0124]

[0125] In formula (15), z 11 and z 12 are percentage variables with a value range of (0,1), and the percentage variable z 11 and z 12 The density P1 of flammable tree species in spring and autumn obtained in S2.1 is processed by the tertile method to obtain the percentage value corresponding to the quantile, P 1max is the maximum continuous value of the spring and autumn shrub layer obtained by S2.1;

[0126] In formulas (13), (14), and (15), the index quantiles can be adjusted according to the actual situation. When the forest stands involved have green cover or do not have green cover, the quantiles can be appropriately adjusted according to the actual situation.

[0127] In S3.1.2, the initial surface fire risk level is determined based on the spring and autumn surface litter layer index value α1 and the spring and autumn shrub layer index value β1, and the spring and autumn initial surface fire risk level is obtained; the specific process is:

[0128] When the index value α1 of the surface litter layer in spring and autumn is not lower than the first threshold and the index value β1 of the shrub layer in spring and autumn is not lower than the second threshold, it is judged as a high risk b of the initial surface fire in spring and autumn; otherwise, it is judged as a low risk a of the initial surface fire in spring and autumn;

[0129] When the spring and autumn shrub layer index value β1 is higher than the second threshold, the value of the first threshold is 1;

[0130] When the spring and autumn shrub layer index value β1 is not higher than the second threshold, the value of the first threshold is 2;

[0131] The value of the second threshold is 2;

[0132] A high shrub layer index value means that the forest floor and lower space are densely covered with shrubs, which become a source of a large amount of flammable materials. When a fire occurs, they can provide more combustible materials and promote the spread of the fire.

[0133] At the same time, a high index value of the shrub layer means enhanced continuity. When the shrub layer is dense, the spatial distance between vegetation is reduced, which increases the continuity of the horizontal and vertical spread of the fire. The flame can more easily jump from one plant to another, accelerating the spread of the fire. When the fire behavior is strong and the shrub layer is dense, more heat can be generated during the combustion process, causing the fire to be more intense. This intense fire behavior may make the fire difficult to control and increase the difficulty of firefighting. When the shrub layer is dense, the height of the flame may increase, making it easier for the flame to contact the upper tree crown, which may cause a more dangerous canopy fire.

[0134] Therefore, when the shrub layer index value is high, the first threshold value of the spring and autumn surface litter layer index value needs to be corrected.

[0135] For example, when the spring and autumn ground litter layer index value α1 = 3, and the spring and autumn shrub layer index value β1 = 2, the first threshold is 3 and the second threshold is 2. When the spring and autumn ground litter layer index value α1 is not lower than the first threshold and the spring and autumn shrub layer index value β1 is not lower than the second threshold, it is judged as high risk b

[0136] group a 11、12、21、31 Group B 22、23、32、33、13

[0137] In S3.1.3, the initial surface fire risk level is corrected according to the spring and autumn forest canopy index value γ1 to obtain the spring and autumn fire hazard level; the specific process is:

[0138] According to the canopy index value γ1 in spring and autumn, the initial low risk of surface fire in spring and autumn a is revised to low risk of fire in spring and autumn, medium-low risk of fire in spring and autumn, and medium-high risk of fire in spring and autumn;

[0139] According to the spring and autumn forest canopy index value γ1, the initial spring and autumn surface fire high risk b is revised to spring and autumn fire medium-low risk, spring and autumn fire medium-high risk, and spring and autumn fire high risk.

[0140] In S3.2.1, the ternary method is used to process the initial fire intensity value I2 of the summer forest fire surface obtained in S2.2 to obtain the summer surface litter layer index value α2; the specific process is:

[0141]

[0142] In formula (16), x 21 and x 22 is a percentage variable with a value range of (0,1), the percentage variable x21 and x 22 The initial fire intensity value I2 of summer forest fire obtained by S2.2 is processed by the tertile method, and the percentage value corresponding to the quantile is obtained, I 2max The maximum initial fire intensity value of summer forest fire surface obtained by S2.2;

[0143] The three-digit method is used to process the summer shrub layer continuous value L2 obtained in S2.2 to obtain the summer shrub layer index value β2; the specific process is:

[0144]

[0145] In formula (17), y 21 and 22 is a percentage variable with a value range of (0,1), the percentage variable y 21 and 22 is the quantile obtained by processing the continuous value L2 of the summer shrub layer obtained by S2.2 using the tertile method, and the corresponding percentage value, L 2max is the maximum continuous value of the summer shrub layer obtained by S2.2;

[0146] The ternary method is used to process the density P2 of the flammable tree species in summer obtained in S2.2 to obtain the summer forest canopy index value γ2; the specific process is:

[0147]

[0148] In formula (18), z 21 and z 22 are percentage variables with a value range of (0,1), and the percentage variable z 21 and z 22 The density P2 of the summer flammable tree species obtained in S2.2 is processed by the tertile method to obtain the percentage value corresponding to the quantile, P 2max is the maximum continuous value of the summer shrub layer obtained by S2.2;

[0149] In formulas (16), (17), and (18), the index quantiles can be adjusted according to the actual situation. In this way, when the forest stands involved have green cover or when the forest stands involved have no green cover, the quantiles can be appropriately adjusted according to the actual situation.

[0150] In S3.2.2, the initial surface fire risk level is determined based on the summer surface litter layer index value α2 and the summer shrub layer index value β2 to obtain the summer initial surface fire risk level; the specific process is:

[0151] When the summer surface litter layer index value α2 is not lower than the third threshold and the summer shrub layer index value β2 is not lower than the fourth threshold, it is judged as a high risk b for initial summer surface fire; otherwise, it is judged as a low risk a for initial summer surface fire;

[0152] When the summer shrub layer index value β2 is higher than the fourth threshold, the value of the third threshold is 1;

[0153] When the summer shrub layer index value β2 is not higher than the fourth threshold, the value of the third threshold is 2;

[0154] The value of the fourth threshold is 2;

[0155] A high shrub layer index value means that the forest floor and lower space are densely covered with shrubs, which become a source of a large amount of flammable materials. When a fire occurs, they can provide more combustible materials and promote the spread of the fire.

[0156] At the same time, a high index value of the shrub layer means enhanced continuity. When the shrub layer is dense, the spatial distance between vegetation is reduced, which increases the continuity of the horizontal and vertical spread of the fire. The flame can jump from one plant to another more easily, accelerating the spread of the fire. When the fire behavior is strong and the shrub layer is dense, more heat can be generated during the combustion process, causing the fire to be more intense. This intense fire behavior may make the fire difficult to control and increase the difficulty of firefighting. When the shrub layer is dense, the height of the flame may increase, making it easier for the flame to contact the upper tree crown, which may cause a more dangerous canopy fire. Therefore, when the shrub layer index value is high, the first threshold value of the surface litter layer index value in spring and autumn needs to be corrected to be more in line with the actual situation.

[0157] For example, when the summer surface litter layer index value α2 = 3 and the summer shrub layer index value β2 = 2, the third threshold is 3 and the fourth threshold is 2. When the summer surface litter layer index value α2 is not lower than the third threshold and the spring and autumn shrub layer index value β2 is not lower than the fourth threshold, it is judged as high risk b;

[0158] group a 11、12、21、31 Group B 22、23、32、33、13

[0159] In S3.2.3, the initial surface fire risk level is corrected according to the summer canopy index value γ2, and the specific process of obtaining the summer fire hazard level is as follows:

[0160] According to the summer canopy index value γ2, the initial low risk of summer surface fire a is revised to low risk of summer fire, medium-low risk of summer fire, and medium-high risk of summer fire.

[0161] According to the size of the summer canopy index value γ2, the initial high risk of summer surface fire b is corrected to medium-low risk of summer fire, medium-high risk of summer fire, and high risk of summer fire.

[0162] Finally, a fire hazard level model prepared according to the present invention is shown in Table 4 below:

[0163] Table 4

[0164] high b3 Medium to high a3, b2 Medium-low a2, b1 Low a1

[0165] In addition, forest fire prevention guidance can be provided according to a forest fire hazard level comparison table 5 prepared according to a fire hazard level model of the present invention:

[0166] Table 5

[0167]

[0168] The other steps and parameters are the same as those in Specific Embodiments 1 to 8.

[0169] Specific implementation method 10: This implementation method is different from specific implementation methods 1 to 9 in that:

[0170] The cold temperate forest data to be evaluated in S4 include: the season of the cold temperate forest to be evaluated, the thickness of the ground litter of the cold temperate forest to be evaluated X3, the density of the shrubs of the cold temperate forest to be evaluated ρ3, the height of the shrubs of the cold temperate forest to be evaluated h3, the calorific value of the ground litter of the cold temperate forest to be evaluated H3, the number of flammable tree species of the cold temperate forest to be evaluated Y3 and the forest area of ​​the cold temperate forest to be evaluated m3;

[0171] In S4, the boreal forest data to be evaluated are collected, and the specific process is as follows:

[0172] The data collectors used a ruler to measure the litter thickness and shrub height of the cold temperate forest to be evaluated, and obtained the surface litter thickness X3 and shrub height h3 of the cold temperate forest to be evaluated;

[0173] Data collectors sampled and counted the number of shrubs, the number of flammable tree species, the forest area and the shrub area in the cold temperate forest to be evaluated, and obtained the shrub density ρ3 of the cold temperate forest to be evaluated and the number of flammable tree species Y3 in a 1-mu sample plot of the cold temperate forest to be evaluated;

[0174] The present invention is highly operable. When investigating forest land on the spot, the measuring tool only needs a ruler. The system inputs the thickness of surface litter, forest land slope, shrub density, shrub height, and density of flammable tree species. The forest fire hazard level of the area and the changes in forest flammability at different periods can be evaluated on the spot. The combination of the three indicators can be appropriately adjusted to realize dynamic evaluation of forest fire hazard. The other steps and parameters are the same as those of the first to ninth embodiments.

[0175] Combined with specific implementations one to ten

[0176] Taking the Greater Khingan Range forest area as an example, Figure 1 As shown, the present invention is further described.

[0177] 1 Historical sampling: Field measurements were conducted on more than 3,000 grid survey plots in the cold-temperate coniferous forest belt to obtain historical forest data; the main flammable tree species in the cold-temperate coniferous forest belt are conifers, including larch, larch, spruce, etc.

[0178] According to the present invention, the potential initial fire intensity index of a certain season is calculated, and the average quantiles are obtained by using the tertile method, which are 22 and 69, and are divided into three levels from small to large, namely, {I│I<22}=1; {I│22≤I≤69}=2; {I│I>69}=3. Where I is the potential initial fire intensity (kW / m)

[0179] The product of shrub density and height of more than 3,000 coniferous forest survey plots in the region was counted, and the average tertile method was used to obtain the shrub density and height product points, which were 3.7 and 10.2, and they were divided into three levels from small to large, namely, {L│L<3.7}=1; {L│3.7≤L≤10.2}=2; {L│L>10.2}=3;

[0180] The density of more than 3,000 coniferous forest survey plots in the area was counted, and the quantiles were 795 and 1337 using the average ternary method, which were divided into three levels from small to large: 1, 2, and 3, that is, {P│P<795}=1; {P│795≤P≤1337}=2; {P│P>1337}=3. Where P is the density of flammable tree species (plants / hm2),

[0181] Construct a fire danger level model based on historical data.

[0182] 2 Actual sampling was conducted to assess the forest fire hazard of a Larix gmelinii forest in a certain area of ​​the region.

[0183] 2.1 Calculation of litter layer indicators and classification

[0184] The thickness of the litter layer combustible material (x) is 2cm; Table 1 shows that the calorific value of Pinus sylvestris is 19225kJ / kg; Table 2 shows that the R0 value of Pinus sylvestris is 0.005; in order to compare at the same meteorological level, the wind speed correction coefficient (Ks) can be taken as the historical average wind speed during the fire prevention period. According to statistics, the average wind speed in the Greater Khingan Range in the past three years is 2.3m / s. Table 3 shows that the Ks value is 1.4; Table 4 shows that the combustible configuration pattern correction coefficient (Ks) of the forest is 1; the slope of the forest is estimated to be 10°. It can be obtained that the potential initial fire intensity index of the area is 306, which is greater than the quantile 69. Therefore, the potential initial fire intensity index is 3.

[0185] 2.2 Calculation of shrub layer indicators and classification

[0186] The number of shrubs per unit area of ​​the forest was measured to be 8, with an average height of 0.5m. The product of the shrub density and the height is 4, that is, 3.7≤x≤10.2, and the index of this layer is 2.

[0187] 2.3 Calculation of canopy index and classification

[0188] The main tree species in this forest is Larix gmelinii, mixed with a small amount of Populus davidiana. Since Populus davidiana is not a flammable tree species, it is only necessary to investigate the density of Larix gmelinii. The field estimate of the density of Larix gmelinii is 1,500 trees / hm2, which is greater than the quantile of 1,337 trees / hm2. Therefore, the flammable tree species density index is 3.

[0189] 3. Evaluate forest fire risk level

[0190] The above measurement and calculation result in a combination of three indicators of 323. By comparing with Table 5, it can be seen that the forest fire hazard of this forest land is at a high level.

[0191] The above only describes the preferred embodiments of the present invention. It should be understood that the present invention is not limited to the above specific implementation methods. Although the present invention has been disclosed as above in the preferred embodiments, it is not used to limit the present invention. Any technician familiar with the profession can make some changes or modify the technical contents disclosed above into equivalent embodiments with equivalent changes without departing from the scope of the technical solution of the present invention. However, any simple modification, equivalent replacement and improvement made to the above embodiments without departing from the content of the technical solution of the present invention, based on the technical essence of the present invention, within the spirit and principles of the present invention, still fall within the protection scope of the technical solution of the present invention.

Claims

1. A method for assessing the risk of forest fires in cold temperate zones, characterized in that: The following steps are involved: S1: Obtain historical boreal forest data; S2: preprocessing the historical cold temperate forest data obtained in S1 to obtain cold temperate forest fire risk assessment parameters; The cold temperate forest fire risk assessment parameters include: cold temperate forest fire risk assessment parameters in spring and autumn The spring and autumn cold temperate forest fire risk assessment parameters include: spring and autumn forest fire surface initial fire intensity value I1, expressed by the formula: I1=HW1R1 (1) Where, I1 is the initial fire intensity of forest fires in spring and autumn; H is the calorific value of surface litter; W1 is the effective fuel load in spring and autumn; R1 is the initial forest fire spread speed in spring and autumn; The calculation formula for the initial forest fire spread speed R1 in spring and autumn described in formula (1) is: In formula (2), R0 is the initial fire spread speed in horizontal windless conditions (m / min), K w is the wind speed correction factor, K S1 is the correction coefficient of fuel allocation pattern in spring and autumn, and θ is the average slope of the forest land; The correction coefficient K of the combustible material configuration pattern in spring and autumn described in formula (2) S1 The calculation formula is: In formula (1), the calculation formula for the effective combustible load W1 in spring and autumn is: W1=A+BX1 (4) In the formula (4), A represents the litter load coefficient of combustible tree species, B represents the litter load thickness coefficient of combustible tree species, and X1 represents the thickness of the litter on the ground surface in spring and autumn; The cold temperate zone forest fire risk assessment parameters also include: summer cold temperate zone forest fire risk assessment parameters, The parameters for calculating the summer cold temperate forest fire risk assessment parameters include: summer combustible configuration pattern correction coefficient K S2 The calculation formula is: In formula (9), X2 represents the thickness of surface litter in summer; S3: constructing a forest fire risk assessment model according to the cold temperate zone forest fire risk assessment parameters; S4: Collect forest data of the boreal forest to be assessed; S5: Inputting the collected cold-temperate forest data to be assessed into a cold-temperate forest fire hazard assessment model, and outputting a cold-temperate forest fire risk level.

2. A method for assessing the risk of cold temperate forest fires according to claim 1, characterized in that: The historical cold temperate forest data in S1 include: spring and autumn historical cold temperate forest data and summer historical cold temperate forest data, and non-seasonal historical cold temperate forest data; The historical cold temperate forest data in spring and autumn include: the thickness of ground litter in spring and autumn X1, the density of shrubs in spring and autumn ρ1, the height of shrubs in spring and autumn h1, and the number of flammable tree species in one mu of sample plot in spring and autumn Y1; The historical cold temperate forest data in summer include: summer ground litter thickness X2, summer shrub density ρ2, summer shrub height h2 and the number of flammable tree species in a 1-acre plot in summer Y2; The non-seasonal historical cold temperate forest data include: average forest slope θ, initial windless spreading speed of litter R0, wind speed correction coefficient K w , combustible tree species litter load coefficient A and combustible tree species litter load thickness coefficient B, and surface litter calorific value H.

3. A method for assessing the risk of cold temperate forest fires according to claim 2, characterized in that: In S2, the historical cold-temperate forest data obtained in S1 are preprocessed to obtain the cold-temperate forest fire risk assessment parameters; the specific process is: S2.1: Obtain the spring and autumn cold temperate forest fire hazard assessment parameters based on the spring and autumn historical cold temperate forest data and the non-seasonal historical cold temperate forest data; S2.2: Based on summer historical boreal forest data and non-seasonal historical boreal forest data, obtain summer boreal forest fire hazard assessment parameters.

4. A method for assessing the risk of forest fires in cold temperate zones according to claim 3, characterized in that: In S2.1, the spring and autumn cold temperate forest fire hazard assessment parameters are obtained based on the spring and autumn historical cold temperate forest data and the non-seasonal historical cold temperate forest data; the spring and autumn cold temperate forest fire hazard assessment parameters also include: the spring and autumn shrub layer continuous value L1, the spring and autumn flammable tree species density P1; the specific process is: S2.1.1: Calculate the continuous value of the shrub layer L1 in spring and autumn; S2.1.2: Calculate the density P1 of flammable tree species in spring and autumn; In S2.2, the summer cold temperate forest fire risk assessment parameters are obtained based on the summer historical cold temperate forest data and the non-seasonal historical cold temperate forest data; the summer cold temperate forest fire risk assessment parameters include: summer forest fire surface initial fire intensity value I2, summer shrub layer continuous value L2, summer flammable tree species density P2, the specific process is: S2.2.1: Calculate the initial fire intensity value I2 of the summer forest fire surface; S2.2.2: Calculate the continuous value of the summer shrub layer, L2; S2.2.3: Calculate the density P2 of tree species that are flammable in summer.

5. A method for assessing the risk of cold temperate forest fires according to claim 4, characterized in that: The calculation formula for the continuous value L1 of the shrub layer in spring and autumn in S2.1.1 is: L1=ρ1×h1 (5) In formula (5), ρ1 represents the density of shrubs in spring and autumn, h1 represents the height of shrubs in spring and autumn; The calculation formula for the density P1 of flammable tree species in spring and autumn in S2.1.2 is: In formula (6), Y1 represents the number of flammable tree species in one mu of sample plot in spring and autumn.

6. A method for assessing the risk of forest fires in cold temperate zones according to claim 5, characterized in that: The specific process of calculating the initial fire intensity value of the summer forest fire surface in S2.2.1 is as follows: I2=HW2R2 (7) Where, I2 is the initial fire intensity of forest fire on the ground in summer; W2 is the effective fuel load in summer; R2 is the initial forest fire spread speed in summer; The calculation formula for the initial forest fire spread speed R2 in summer described in formula (7) is: In formula (8), R0 is the initial fire spread speed in horizontal windless state (m / min), K w is the wind speed correction factor, K S2 is the correction coefficient of summer fuel configuration pattern, θ is the average slope of the forest land; In formula (7), the calculation formula for the effective combustible load W2 in summer is: W2=A+BX2 (10) In the formula (10), A represents the litter load coefficient of combustible tree species, B represents the litter load thickness coefficient of combustible tree species, and X2 represents the litter thickness on the ground in summer; The calculation formula for the continuous value L2 of the summer shrub layer in S2.2.2 is: L2=ρ2×h2 (11) In formula (11), ρ2 represents the summer shrub density, h2 represents the summer shrub height; The calculation formula for the density P2 of flammable tree species in summer in S2.2.3 is: In formula (12), Y2 represents the number of flammable tree species in one mu of plot in summer.

7. A method for assessing the risk of cold temperate forest fires according to claim 6, characterized in that: The forest fire risk assessment model in S3 includes a spring and autumn forest fire risk assessment model and a summer forest fire risk assessment model; the forest fire risk assessment model is constructed according to the cold temperate zone forest fire risk assessment parameters; the specific process is: S3.1: Construct a spring and autumn forest fire risk assessment model based on the spring and autumn cold temperate forest fire risk assessment parameters; S3.2: Construct a summer forest fire hazard assessment model based on the summer cold temperate zone forest fire hazard assessment parameters.

8. A method for assessing the risk of forest fires in cold temperate zones according to claim 7, characterized in that: In S3.1, a spring and autumn forest fire risk assessment model is constructed based on the spring and autumn cold temperate zone forest fire risk assessment parameters; the specific process is: S3.1.1: The initial fire intensity value I1 of forest fires on the ground in spring and autumn obtained in S2.1 is processed by the tertile method to obtain the index value α1 of the litter layer on the ground in spring and autumn; The continuous value L1 of the spring and autumn shrub layer obtained by S2.1 was processed using the tertile method to obtain the index value β1 of the spring and autumn shrub layer; The density P1 of flammable tree species in spring and autumn obtained by S2.1 was processed using the tertile method to obtain the index value γ1 of the forest canopy in spring and autumn; S3.1.2: Based on the spring and autumn surface litter layer index value α1 and the spring and autumn shrub layer index value β1, the initial surface fire risk level is determined to obtain the spring and autumn initial surface fire risk level; S3.1.3: According to the spring and autumn forest canopy index value γ1, the initial surface fire risk level is corrected to obtain the spring and autumn fire hazard level; In S3.2, a summer forest fire risk assessment model is constructed based on the summer cold temperate zone forest fire risk assessment parameters. The specific process is as follows: S3.2.1: Use the tertile method to process the initial fire intensity value I2 of the summer forest fire surface obtained in S2.2 to obtain the summer surface litter layer index value α2; The continuous value L2 of the summer shrub layer obtained by S2.2 was processed using the tertile method to obtain the summer shrub layer index value β2; The density P2 of flammable tree species in summer obtained by S2.2 was processed using the tertile method to obtain the summer forest canopy index value γ2; S3.2.2: Based on the summer surface litter layer index value α2 and the summer shrub layer index value β2, the initial surface fire risk level is determined to obtain the summer initial surface fire risk level; S3.2.3: Based on the summer canopy index value γ2, the initial surface fire risk level is corrected to obtain the summer fire hazard level.

9. A method for assessing the risk of cold temperate forest fires according to claim 8, characterized in that: In S3.1.1, the ternary method is used to process the initial fire intensity value I1 of the forest fire surface in spring and autumn obtained in S2.1 to obtain the index value α1 of the litter layer on the surface in spring and autumn. The specific process is as follows: In formula (13), x 11 and x 12 is a percentage variable with a value range of (0,1), the percentage variable x 11 and x 12 The initial fire intensity value I1 of forest fires in spring and autumn obtained by S2.1 is processed by the tertile method to obtain the percentage value corresponding to the quantile, I 1max is the maximum initial fire intensity value of forest fires on the ground in spring and autumn obtained in S2.1; The tertile method is used to process the spring and autumn shrub layer continuous value L1 obtained in S2.1 to obtain the spring and autumn shrub layer index value β1; the specific process is: In formula (14), y 11 and 12 is a percentage variable with a value range of (0,1), the percentage variable y 11 and 12 is the quantile obtained by processing the continuous value L1 of the spring and autumn shrub layer obtained in S2.1 using the tertile method, and the corresponding percentage value, L 1max is the maximum continuous value of the spring and autumn shrub layer obtained by S2.1; The ternary method is used to process the density P1 of flammable tree species in spring and autumn obtained in S2.1 to obtain the spring and autumn forest canopy index value γ1; the specific process is: In formula (15), z 11 and z 12 are percentage variables with a value range of (0,1), and the percentage variable z 11 and z 12 The density P1 of flammable tree species in spring and autumn obtained in S2.1 is processed by the tertile method to obtain the percentage value corresponding to the quantile, P 1max is the maximum continuous value of the spring and autumn shrub layer obtained by S2.1; In S3.1.2, the initial surface fire risk level is determined based on the spring and autumn surface litter layer index value α1 and the spring and autumn shrub layer index value β1, thereby obtaining the spring and autumn initial surface fire risk level; The specific process is: When the index value α1 of the surface litter layer in spring and autumn is not lower than the first threshold and the index value β1 of the shrub layer in spring and autumn is not lower than the second threshold, it is judged as a high risk b of the initial surface fire in spring and autumn; otherwise, it is judged as a low risk a of the initial surface fire in spring and autumn; When the spring and autumn shrub layer index value β1 is higher than the second threshold, the value of the first threshold is 1; When the spring and autumn shrub layer index value β1 is not higher than the second threshold, the value of the first threshold is 2; The value of the second threshold is 2; In S3.1.3, the initial surface fire risk level is corrected according to the spring and autumn forest canopy index value γ1 to obtain the spring and autumn fire hazard level; the specific process is: According to the canopy index value γ1 in spring and autumn, the initial low risk of surface fire in spring and autumn a is revised to low risk of fire in spring and autumn, medium-low risk of fire in spring and autumn, and medium-high risk of fire in spring and autumn; According to the spring and autumn forest canopy index value γ1, the initial spring and autumn surface fire high risk b is revised to spring and autumn fire medium-low risk, spring and autumn fire medium-high risk, and spring and autumn fire high risk. In S3.2.1, the ternary method is used to process the initial fire intensity value I2 of the summer forest fire surface obtained in S2.2 to obtain the summer surface litter layer index value α2; the specific process is: In formula (16), x 21 and x 22 is a percentage variable with a value range of (0,1), the percentage variable x 21 and x 22 The initial fire intensity value I2 of summer forest fire obtained by S2.2 is processed by the tertile method, and the percentage value corresponding to the quantile is obtained, I 2max The maximum initial fire intensity value of summer forest fire surface obtained by S2.2; The three-digit method is used to process the summer shrub layer continuous value L2 obtained in S2.2 to obtain the summer shrub layer index value β2; the specific process is: In formula (17), y 21 and 22 is a percentage variable with a value range of (0,1), the percentage variable y 21 and 22 is the quantile obtained by processing the continuous value L2 of the summer shrub layer obtained by S2.2 using the tertile method, and the corresponding percentage value, L 2max is the maximum continuous value of the summer shrub layer obtained by S2.2; The ternary method is used to process the density P2 of the flammable tree species in summer obtained in S2.2 to obtain the summer forest canopy index value γ2; the specific process is: In formula (18), z 21 and z 22 are percentage variables with a value range of (0,1), and the percentage variable z 21 and z 22 The density P2 of the summer flammable tree species obtained in S2.2 is processed by the tertile method to obtain the percentage value corresponding to the quantile, P 2max is the maximum continuous value of the summer shrub layer obtained by S2.2; In S3.2.2, the initial surface fire risk level is determined based on the summer surface litter layer index value α2 and the summer shrub layer index value β2 to obtain the summer initial surface fire risk level; The specific process is: When the summer surface litter layer index value α2 is not lower than the third threshold and the summer shrub layer index value β2 is not lower than the fourth threshold, it is judged as a high risk b for initial summer surface fire; otherwise, it is judged as a low risk a for initial summer surface fire; When the summer shrub layer index value β2 is higher than the fourth threshold, the value of the third threshold is 1; When the summer shrub layer index value β2 is not higher than the fourth threshold, the value of the third threshold is 2; The value of the fourth threshold is 2; In S3.2.3, the initial surface fire risk level is corrected according to the summer canopy index value γ2, and the specific process of obtaining the summer fire hazard level is as follows: According to the summer canopy index value γ2, the initial low risk of summer surface fire a is revised to low risk of summer fire, medium-low risk of summer fire, and medium-high risk of summer fire. According to the size of the summer canopy index value γ2, the initial high risk of summer surface fire b is corrected to medium-low risk of summer fire, medium-high risk of summer fire, and high risk of summer fire.

10. A method for assessing the risk of cold temperate forest fires according to claim 9, characterized in that: The cold temperate forest data to be evaluated in S4 include: the season of the cold temperate forest to be evaluated, the thickness of the ground litter of the cold temperate forest to be evaluated X3, the density of the shrubs of the cold temperate forest to be evaluated ρ3, the height of the shrubs of the cold temperate forest to be evaluated h3, the calorific value of the ground litter of the cold temperate forest to be evaluated H3, the number of flammable tree species of the cold temperate forest to be evaluated Y3 and the forest area of ​​the cold temperate forest to be evaluated m3; In S4, the boreal forest data to be evaluated are collected, and the specific process is as follows: The data collectors used a ruler to measure the litter thickness and shrub height of the cold temperate forest to be evaluated, and obtained the surface litter thickness X3 and shrub height h3 of the cold temperate forest to be evaluated; The data collectors sampled and counted the number of shrubs, the number of flammable tree species, the forest area and the shrub area in the cold-temperate forest to be evaluated, and obtained the shrub density ρ3 of the cold-temperate forest to be evaluated and the number of flammable tree species Y3 in a 1-acre sample plot of the cold-temperate forest to be evaluated.

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