CN114360214B - Extra-large scale glacier debris flow early warning method - Google Patents
Extra-large scale glacier debris flow early warning method Download PDFInfo
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Abstract
The invention relates to the field of geological disaster early warning, discloses an extra-large scale glacier debris flow early warning method, and solves the problems of low early warning precision and difficulty in implementation of an early warning scheme in the prior art. The method comprises the following steps: s1, calculating the material energy parameters of the regional watershed, and screening the glacier debris watershed needing to be monitored in a key way; s2, analyzing and calculating water source factors of the glacier debris flow basin monitored at the heavy point, wherein the water source factors comprise air temperature, precipitation and snow water equivalent of a debris flow forming area; s3, based on the parameters obtained by calculation in the step S2, carrying out catastrophe climate judgment and catastrophe weather judgment in sequence by utilizing the extra-large scale glacier debris flow catastrophe climate judgment model and the catastrophe weather judgment model; if the variable weather judgment condition and the catastrophe weather judgment condition are both met, the early warning condition is met; and S4, carrying out debris flow disaster alarm on the glacier debris flow watershed meeting the early warning condition.
Description
Technical Field
The invention relates to the field of geological disaster early warning, in particular to an extra-large scale glacier debris flow early warning method.
Background
The glacier debris flow is one of special geological disaster types in high-altitude mountain areas, in particular to the glacier debris flow with super-large scale (more than 50 multiplied by 10)4m3) And serious threats are caused to economic development and resident safety in high-altitude mountain areas. The formation of glacier debris flow in high-altitude mountainous areas is different from the formation of debris flow in general mountainous areas, and the water source excitation condition is influenced by ice and snow melting water besides rainfall. The glacier debris flow can be effectively monitored and early warned in the high-altitude mountain area only by comprehensively considering the coupling triggering influence of channel terrain, loose sources in the channel and rainfall and ice and snow melting water.
At present, the early warning scheme for glacier debris flow disaster construction mainly comprises:
the patent application is 202110532903.4 and is named as a glacier debris flow area early warning method based on hydro-thermal combination, and an early warning model is obtained by utilizing accumulated temperature and accumulated rainfall statistics, wherein the accumulated temperature cannot objectively reflect the situations of accumulated snow and ablation of glacier in a glacier debris flow channel, and the early warning precision of the glacier debris flow disaster is limited;
the patent application with the application number of 202110154503.4 and the name of glacier debris flow disaster early warning method based on the pregnant disaster background adopts a plurality of index parameters, such as glacier variable quantity, avalanche accumulation quantity and glacier and avalanche daily variable quantity, so that the obtaining is difficult, and the early warning work is difficult to implement.
In addition, the temperature and rainfall data adopted by the above patent are both derived from the near meteorological observation station or the regional remote sensing data, the data can have great difference with the meteorological conditions of a debris flow formation region when being directly used, the scale of the applicable glacier debris flow disaster is not distinguished on the early warning disaster object, the early warning result is deviated due to the fuzzy disaster sample, and the early warning target is undefined and cannot carry out the disaster emergency disposal work with pertinence.
Disclosure of Invention
The technical problem to be solved by the invention is as follows: the early warning method for the glacier debris flow in the super-large scale is provided, and the problems that the early warning precision is low and the implementation is difficult in the early warning scheme in the prior art are solved.
The technical scheme adopted by the invention for solving the technical problems is as follows:
the early warning method for the glacier debris flow on the extra-large scale is characterized by comprising the following steps of:
s1, calculating material energy parameters of each glacial debris flow basin in the monitoring area range according to the longitudinal slope ratio of the main ditch of the glacial debris flow basin and loose material sources, and screening the glacial debris flow basin needing to be monitored in a key mode according to the material energy parameters;
s2, respectively analyzing and calculating water source factors of the glacier debris flow basin monitored at the heavy point, wherein the water source factors comprise the air temperature, precipitation and snow water equivalent of a debris flow forming area;
s3, based on the result of the water source factor analysis and calculation in the step S2, carrying out catastrophe weather judgment by utilizing the extra-large scale glacier debris flow catastrophe weather judgment model, and carrying out catastrophe weather judgment by utilizing the extra-large scale glacier debris flow catastrophe weather judgment model; if the catastrophe climate judgment and the catastrophe weather judgment both meet the corresponding catastrophe climate judgment condition and catastrophe weather judgment condition, the early warning condition is met, otherwise, the early warning condition is not met;
and S4, carrying out debris flow disaster alarm on the glacier debris flow watershed meeting the early warning condition.
Further, the step S1 includes:
s11, interpreting and identifying the range of the loose object sources distributed in the flow field based on the optical remote sensing image, and calculating the area of the loose object sources according to the identified rangeμ i The bulk source comprises a moraine and a paleo;
s12, extracting the range of the drainage basin and the height difference from the highest point of the channel forming area to the channel opening by using the digital elevation modelhAnd the horizontal distance from the highest point of the channel formation region to the trench openingl(ii) a Calculating the area of the drainage basin according to the range of the drainage basinArea basin Calculating the longitudinal slope gradient ratio of the main trench according to the height difference and the horizontal distances：s=h/l×100%；
S13, calculating material energy parameters including main ditch longitudinal slope ratio reduction normalization indexσ i And main furrow loose source indexM i ：
Wherein the content of the first and second substances,s i for the current calculation of the main trench longitudinal slope gradient of the watershed,s j is as followsThe longitudinal slope ratio drop of the main ditch of the sub-basin in the main basin where the basin is located is calculated before,nfor the current calculation of the number of sub-domains within the parent domain to which the domain belongs,μ i to currently calculate the loose source area of the watershed,icalculating the serial number of the current basin;
s14, calculating the material energy value of the watershed according to the material energy parameterE i ：
E i = k 1 σ i +k 2 M i
Wherein the content of the first and second substances,k 1 、k 2 is a weighting coefficient;
s15, calculating the energy value of the materialE i And judging the glacier debris flow basin which is larger than the preset energy condition threshold of the glacier debris flow material with the extra-large scale as the glacier debris flow basin needing to be monitored in a key way.
Further, the step S2 includes:
s21, performing regional air temperature interpolation on the target basin;
s22, local air temperature correction is carried out based on the regional air temperature interpolation and the air temperature observation data of the monitoring points;
s23, acquiring regional precipitation inversion data;
s24, local precipitation correction is carried out based on the regional precipitation inversion data and the rainfall observation data of the monitoring points;
s25, acquiring regional snow inversion data;
and S26, calculating the regional total snow water equivalent based on the regional snow inversion data.
Specifically, in step S21, the performing the region air temperature interpolation on the target basin specifically includes:
carrying out regional air temperature interpolation on the target basin based on a thin-plate smooth spline interpolation method by utilizing daily air temperature observation data of an adjacent meteorological station of the target basin and topographic data of the target basin:
T i = f（x i ）+bT y i +e i
wherein the content of the first and second substances,T i for meshes within a target stream domainiAs a result of the interpolation of the air temperature,f（x i ）is a gridx i B is a terrain covariate coefficient,y i is a gridx i Elevation value of e i Is a random error.
Specifically, in step S22, the performing the local air temperature correction based on the zone air temperature interpolation and the monitoring point air temperature observation data specifically includes:
s221, acquiring day-by-day air temperature observation data of the monitoring stations through air temperature monitoring equipment installed at each monitoring station of the target basint i And is connected with the grid to which the monitoring station belongsx i Result of air temperature interpolationT i Calculating difference to obtain single point temperature correction value of temperature interpolation and observation valueR Ti ；
S222, temperature correction value based on each monitored station in target flow domainR Ti Constructing a Thiessen polygon, performing spatial interpolation, and generating local air temperature correction dataR T ；
S223, the regional air temperature interpolation result and the local air temperature correction dataR T Adding after unifying the resolution, calculating to obtain local temperature optimization dataT R 。
Specifically, in step S23, regional precipitation inversion data are obtained based on the global precipitation remote sensing data GPM or TRMMP。
Specifically, in step S24, the performing local precipitation correction based on the regional precipitation inversion data specifically includes:
s241, acquiring day-by-day rainfall data of monitoring points through rainfall monitoring equipment installed at each monitoring point of the target drainage basinp i Extracting regional precipitation dataPGrid to which middle monitoring point belongsx i Precipitation inversion data ofP i Through and day-by-day rainfall datap i Obtaining local rainfall correction value by differenceR Pi ；
S242, rainfall correction data obtained based on monitoring stations of target drainage basinR Pi Building Thiessen polygons and carrying out spatial interpolation to generate local precipitation correction dataR P ；
S243, inverting data of regional precipitationPAnd local precipitation correction dataR P Adding after unifying the resolution, and calculating to obtain local precipitation optimization dataP R 。
Specifically, in step S25, the acquiring region snow inversion data specifically includes:
obtaining the snow cover area of the debris flow forming area of the target watershed through the interpretation of the MODIS day-by-day snow dataArea snow And obtaining the snow thickness of the snow accumulation area by using AMSR-E microwave snow depth dataDepth snow 。
Specifically, in step S26, the calculating the area total snow water equivalent based on the area snow inversion data specifically includes:
first, the equivalent of snow water in unit area is calculatedSWE：
Wherein the content of the first and second substances,Depth s_k is as followskThe depth of the accumulated snow in the day,ρ w which is indicative of the density of the water,ρ 0 the density of the fresh accumulated snow is the density,SD k is as followskThe depth of the snow in the day is,ρ s_k is the firstkThe density of the snow in the day is,nrepresents the number of days from the current day of target basin monitoring to the start day of its neighboring winter half year.
Further, in step S3, the catastrophe climate determination model for the extra-large scale glacier debris flow is:
s31, calculating the target basin monitoring time from the current day to the next dayIn the time interval of the beginning day of the next winter half year, the temperature accumulation index lambda and the snow water equivalent basin ratio of the debris flow forming areaSA；
S32, calculating the temperature accumulation index lambda and the snow water equivalent basin ratio of the current year of disaster occurrence and the year adjacent to the current year of disaster occurrence and without disaster occurrence based on the disaster history sampleSATaking the beginning date of the winter half year adjacent to the disaster occurrence date as a starting date, wherein the time interval of adjacent years is the interval from the starting date of the current Gregorian year to the starting date of the previous Gregorian year, and the time interval of the disaster occurrence current year is the interval from the starting date to the disaster occurrence current day;
s33, constructing equivalent river basin ratio of snow waterSAThe data of the current year of disaster occurrence and the year adjacent to the current year of disaster occurrence and in which no disaster occurs are projected to the two-dimensional space, and regression analysis is performed;
s34, obtaining the temperature accumulation index lambda and the snow water equivalent basin ratio based on the step S31SAAnd judging whether the climate condition of the target basin meets the climate condition of the outbreak of the extra-large scale glacier debris flow or not according to the analysis result obtained in the step S33.
Specifically, the calculation method of the temperature accumulation index λ of the debris flow formation area comprises the following steps:
wherein the content of the first and second substances,ATforming effective accumulated temperature of a region for the debris flow, and optimizing data by daily temperature in a specified time intervalT R Accumulating to obtain, if the temperature is normal temperature, accumulating, otherwise, not accumulating;Dthe number of days of positive temperature accumulated in a specified time interval;kis a regression fitting coefficient;
the designated time interval is the time interval designated in step S31 and step S32.
Specifically, in step S31, the snow-water equivalent flow area ratio of the debris flow formation areaSAThe calculating method comprises the following steps:
wherein the content of the first and second substances,SnowMass accum for the cumulative equivalent of snow water in a given time interval, by the equivalent of snow water per unit areaSWEAccumulated calculation is carried out;Area snow forming accumulated snow coverage area for debris flow forming area;daysrepresents the number of valid days within a specified time interval; ΔSWEThe difference between the equivalent quantity of the snow water of the next day and the equivalent quantity of the snow water of the previous day is counted into the equivalent quantity of the accumulated snow water if the difference is a positive number, and the accumulated snow water is not counted if the difference is a negative number, which indicates that no newly added snow quantity exists; the designated time interval is the time interval designated in step S31 and step S32.
Specifically, the regression analysis in step S33 is to solve the optimal segmentation hyperplane of the two-dimensional space; in the step S34, the temperature accumulation index lambda and the snow water equivalent basin ratio are obtained based on the step S31SAAccording to the two-dimensional space optimal segmentation hyperplane obtained in the step S33, whether the climate condition of the target basin meets the climate condition of the outbreak of the extra-large scale glacier debris flow is judged, which specifically includes:
according to the accumulated temperature index lambda and the equivalent river basin ratio of the snow water of the target river basinSACalculating a catastrophe climate decision factorT D-year ：
T D-year = k 3 SA+k 4 λ
Wherein the content of the first and second substances,k 3 、k 4 is the temperature accumulation index lambda and the snow water equivalent basin ratioSAFitting coefficients of the optimal segmentation lines of the constructed two-dimensional space;
setting a catastrophe climate threshold value according to a maximum geometric interval of a two-dimensional spaceT y-threshold ：
Wherein the content of the first and second substances,w、bdividing a plane parameter for the minimum vector distance of the two-dimensional space of the disaster occurrence sample and the non-occurrence sample;
determination factor for determining catastrophe climateT D-year And catastrophe climate thresholdT y-threshold If the magnitude relation of (1) is satisfiedT D-year ＞T y-threshold And judging that the climate conditions of the glacier debris flow outbreak in extra large scale are met.
Further, in step S3, the catastrophe meteorological determination model for the extra-large scale glacier debris flow is:
s35, calculating the average air temperature of the target basin debris flow formation area in about 30 daysT Ave30 And accumulated rainfallP Acc30 ；
S36, calculating the average temperature of the catastrophe day near 30 days based on the disaster history sampleT Ave30 And accumulated rainfallP Acc30 Calculating the average temperature of the same period adjacent to the current year of disaster occurrence and the year of no disaster occurrenceT Ave30 And accumulated rainfallP Acc30 ；
S37, constructing average air temperatureT Ave30 And accumulated rainfallP Acc30 The data of the current year of the disaster and the data of the year adjacent to the current year of the disaster without the disaster are projected to the two-dimensional space, and regression analysis is carried out;
s38, based on the average air temperature obtained in the step S35T Ave30 And accumulated rainfallP Acc30 And judging whether the meteorological conditions of the target basin accord with the meteorological conditions of the outbreak of the extra-large scale glacier debris flow or not according to the analysis result obtained in the step S37.
Specifically, in step S35, the average temperature in the near 30 daysT Ave30 And accumulated rainfallP Acc30 The calculation method comprises the following steps:
wherein the content of the first and second substances,T Ri andP Ri respectively a debris flow forming areaiThe daily optimized air temperature value and the optimized rainfall value.
Specifically, the regression analysis in step S37 is to solve the optimal segmentation hyperplane of the two-dimensional space; in step S38, the average air temperature is obtained based on the average air temperature obtained in step S35T Ave30 And accumulated rainfallP Acc30 And judging whether the meteorological conditions of the target basin meet the meteorological conditions of the outbreak of the glacier debris flow with the extra-large scale according to the two-dimensional space optimal segmentation hyperplane obtained in the step S37, and the method specifically comprises the following steps:
according to the target basin average air temperatureT Ave30 And accumulated rainfallP Acc30 Calculating a catastrophe weather determination factorT D-day ：
T
D-day
= k
5
P
Acc30
+k
6
T
Ave30
Wherein the content of the first and second substances,k 5 、k 6 is the average air temperatureT Ave30 And accumulated rainfallP Acc30 Fitting coefficients of the optimal segmentation lines of the constructed two-dimensional space;
setting a catastrophe meteorological threshold according to a maximum geometric interval of a two-dimensional spaceT d-threshold ：
Wherein the content of the first and second substances,w、bdividing a plane parameter for the minimum vector distance of the two-dimensional space of the disaster occurrence sample and the non-occurrence sample;
determining a catastrophe weather determination factorT D-day And a catastrophe meteorological thresholdT d-threshold If the magnitude relation of (1) is satisfiedT D-day ＞T d-threshold And judging that the extreme large scale glacier debris flow outbreak meteorological conditions are met.
The invention has the beneficial effects that:
based on the sampling data of the extra-large scale glacier debris flow which has been outbreak in the high-altitude mountain area, the weather and weather dual characteristics formed by the extra-large scale glacier debris flow are respectively calculated by fully utilizing the data of the glacier accumulated snow in the glacier debris flow channel on the basis of acquiring the air temperature and rainfall data of the debris flow channel forming area through high-precision interpolation.
Drawings
Fig. 1 is a flow chart of the extra-large scale glacier debris flow early warning method in the invention.
Detailed Description
The invention aims to provide a glacier debris flow early warning method on an extra-large scale, and solves the problems of low early warning precision and difficulty in implementation of an early warning scheme in the prior art. As shown in fig. 1, the scheme includes: s1, calculating the material energy parameter: completing the calculation of regional range watershed material energy parameters, and screening the glacial debris flow watershed needing key monitoring by using a typical glacial debris flow material energy regression judgment model; s2, analyzing and calculating water source factors: performing water source factor analysis calculation on the glacier debris flow which is monitored in a key way, wherein the water source factor analysis calculation comprises calculation of air temperature, precipitation and snow water equivalent of a debris flow forming area; s3, early warning analysis and calculation: taking the generated extra-large scale glacier debris flow as sample data, analyzing to obtain an extra-large scale glacier debris flow catastrophe climate determination model and a catastrophe meteorological determination model, and sequentially performing catastrophe climate determination and catastrophe meteorological determination based on calculation parameters of water source factor analysis; s4, alarming: and alarming the single event which simultaneously meets the determination conditions of the catastrophe climate and the meteorological threshold.
The embodiment is as follows:
the extra-large scale glacier debris flow early warning method in the embodiment comprises the following implementation steps:
s1, calculating a material energy parameter:
s11, interpreting and identifying the range of the loose object source distributed in the flow field by using the high-resolution optical remote sensing image with the resolution ratio of more than 1m, and calculating the area of the loose object source according to the identified rangeμ i The bulk source comprises a tillite and a superlative;
s12, extracting the range of the drainage basin and the height difference from the highest point of the channel forming area to the channel mouth by using a digital elevation model with the topographic precision superior to 1:5 ten thousandhAnd the horizontal distance from the highest point of the channel formation region to the trench openingl(ii) a Calculating the area of the drainage basin according to the range of the drainage basinArea basin Calculating the longitudinal slope gradient ratio of the main trench according to the height difference and the horizontal distances：
s=h/l×100%
S13, calculating material energy parameters including main ditch longitudinal slope ratio reduction normalization indexσ i And main furrow loose source indexM i ：
Wherein the content of the first and second substances,s i for the current calculation of the main trench longitudinal slope gradient of the watershed,s j for the current calculation of the main ditch longitudinal slope gradient of the sub basin in the main basin where the basin is located,nfor the current calculation of the number of sub-domains within the parent domain to which the domain belongs,μ i to currently calculate the loose source area of the watershed,icalculating the serial number of the basin for the current time;
s14, calculating the material energy value of the watershed according to the material energy parameterE i ：
E i = k 1 σ i +k 2 M i
Wherein the content of the first and second substances,k 1 、k 2 is a weighting coefficient;
s15, calculating the energy value of the materialE i And judging the glacier debris flow basin which is larger than the preset energy condition threshold of the glacier debris flow material with the extra-large scale as the glacier debris flow basin needing to be monitored in a key way.
According to the sample data of the great disasters and the engineering prevention and control experience,k 1 =1，k 2 =60.83, the mass energy condition threshold for a very large scale glacier debris flow is 59. That is, to determineE i The debris flow gully more than 59 has the material energy condition of outbreak of extra-large scale glacier debris flow, namely the glacier debris flow gully needing important monitoring.
S2, analyzing and calculating water source factors:
s21, utilizing the daily air temperature observation data of the meteorological station of the adjacent country of the target basin and the topographic data superior to 1:5 ten thousand, carrying out regional air temperature interpolation on the glacier debris basin needing to be monitored in a key way based on a thin disc smooth spline interpolation method, and calculating to generate a regional air temperature interpolation result with the resolution of the target basin superior to 5 m. The thin disk smooth spline interpolation formula is as follows:
T i = f（x i ）+bT y i +e i
wherein the content of the first and second substances,T i for meshes within a target stream domainiAs a result of the interpolation of the air temperature,f（x i ）is a gridx i B is a terrain covariate coefficient,y i is a gridx i Elevation value of e i Is a random error;
s22, installing more than 3 air temperature monitoring devices in the drainage basin to be monitored to obtain the grids to which the monitoring points belongx i Day by day temperature observation datat i And is connected to the monitoring pointx i Result of temperature interpolationT i Subtracting to obtain single-point temperature correction value of temperature interpolation and observation valueR Ti ；
S23 rainfall correction data obtained based on each monitoring stationR Ti Constructing a spatial Thiessen polygon, and performing spatial interpolation to generate local air temperature correction data with the resolution ratio superior to 5mR T ；
S24, interpolating the regional air temperatureTAnd local air temperature correction dataR T Adding after unifying the resolution, calculating to obtain local air temperature optimization dataT R ；
S25, obtaining regional precipitation inversion data by using global precipitation remote sensing data GPM or TRMMP；
S26, installing more than 3 rainfall monitoring devices in the drainage basin to be monitored to obtain the grids to which the monitoring points belongx i Day-by-day rainfall datap i And extracting regional rainfall data through rainfall monitoring pointsPGrid to which middle monitoring point belongsx i Remote sensing precipitation inversion dataP i By passingp i AndP i subtracting to obtain local rainfall correction valueR Pi ；
S27, obtaining based on each monitoring stationObtained rainfall correction dataR Pi Constructing a spatial Thiessen polygon, and performing spatial interpolation to generate regional precipitation correction data with resolution ratio superior to 5mR P ；
S28 inversion data of regional precipitationPAnd locally correcting the dataR P Adding after unifying the resolution, and calculating to obtain local precipitation optimization dataP R ；
S29, obtaining snow cover area of monitoring drainage basin forming area by using MODIS daily snow product interpretationArea snow And obtaining the snow thickness of the snow accumulation area by using AMSR-E microwave snow depth dataDepth snow ；
S210, calculating the equivalent of snow water in unit areaSWEThe formula is as follows:
wherein the content of the first and second substances,Depth s_k is as followskThe depth of the accumulated snow in the day,ρ w which is indicative of the density of the water,ρ 0 the density of the fresh accumulated snow is the density,SD k is as followskThe depth of the snow in the day is,ρ s_k is the firstkThe density of the snow in the day is,nindicating the number of days from the current day of target basin monitoring to the start day of its adjacent winter half year. In the high altitude mountain area, the climate characteristics are divided into winter half year and summer half year, and in the high altitude mountain area in Sichuan, the winter half year is 9 months to 2 months next year, and the summer half year is 3 months to 8 months.
S3, early warning analysis and calculation:
the temperature build-up index λ is defined as follows:
wherein lambda is the accumulated temperature index of the debris flow formation area,ATforming effective accumulated temperature of the region for debris flow, and optimizing data by day-to-day temperature in a specified time intervalT R Accumulating to obtain, if the temperature is positive temperature, accumulating, otherwise, not accumulating;Dfor a given time interval of accumulated days of orthotemperature,kare regression fit coefficients.
Accumulated snow water equivalent of accumulated snow in debris flow formation area is accumulated and calculated day by using snow water equivalent in single daySnowMass accum And defining the equivalent river basin ratio of snow waterSA：
Wherein the content of the first and second substances,SnowMass accum for the cumulative equivalent of snow water in a given time interval, by the equivalent of snow water per unit areaSWEAccumulated calculation is carried out;Area snow forming accumulated snow coverage area for debris flow forming area;daysrepresenting the effective days in the specified time intervalSWEThe difference between the equivalent quantity of the snow water of the next day and the equivalent quantity of the snow water of the previous day is counted into the equivalent quantity of the accumulated snow water if the difference is a positive number, and the accumulated snow water is not counted if the difference is a negative number, which indicates that no newly added snow quantity exists.
Optimizing data based on local air temperatureT R Calculating the average temperature of the near 30 days in the debris flow formation regionT Ave30 Optimizing data based on local precipitationP R Calculating the accumulated rainfall of the debris flow in nearly 30 daysP Acc30 ：
Wherein the content of the first and second substances,T Ri andP Ri respectively a debris flow forming areaiThe daily optimized air temperature value and the optimized rainfall value.
S31, calculating the temperature accumulation index lambda and the equivalent river basin ratio of the snow water in the debris flow forming area in the time interval from the target river basin monitoring day to the start day of the adjacent winter half yearSA。
S32, calculating the temperature accumulation index lambda and the snow water equivalent basin ratio of the disaster occurring year, the period adjacent to the disaster occurring year and the period without the disaster occurring year based on the disaster history sampleSAAnd taking the beginning date of the winter half year adjacent to the disaster occurrence date as the starting date, wherein the time interval of the adjacent years is the interval from the starting date of the current calendar year to the starting date of the previous calendar year, and the time interval of the disaster occurrence current year is the interval from the starting date to the disaster occurrence current date.
The beginning date of the winter half year next to the disaster occurrence date, that is: when the disaster occurrence day is in summer and half year, the disaster occurrence day is the initial day of the last winter and half year; when the disaster occurrence date is within the winter half year, it is the initial date of the winter half year.
Meanwhile, since the winter half year is usually a cross-domain calendar year, the start and stop of the time interval of the adjacent years are defined by the date of the starting date, and the annual time interval is an interval from the starting date of the current calendar year to the starting date of the previous calendar year. Taking the adjacent previous year as an example, the interval from the starting date to the same day of the previous gregorian calendar year, and so on.
Data of the years without disasters can be only one year or can be years, but adjacent years are required to ensure the similarity of the climate. In the subsequent verification process, all the disasters occur in the previous year of the current year.
S33, constructing equivalent river basin ratio of snow waterSAAnd a two-dimensional space with the temperature accumulation index lambda, projecting data of the current year of disaster occurrence and the year adjacent to the current year of disaster occurrence and without disaster occurrence to the two-dimensional space, and solving the two-dimensional space by using an SVM (support vector machine)An optimal segmentation hyperplane of a space, the optimal segmentation hyperplane having a formula:
w T x i +y i +b=0
wherein the content of the first and second substances,w、bfor optimal segmentation of the hyperplane coefficients,x i for two-dimensional space disaster sample pointsxA set of axis coordinates is set for each of the axes,y i for two-dimensional space disaster sample pointsyAn axis coordinate set; snow water equivalent basin ratioSAAnd temperature build-up index λ, andxymay be arbitrary, and in the subsequent verification process, λ isx，SAIs composed ofy。
S34, obtaining the temperature accumulation index lambda and the snow water equivalent basin ratio based on the step S31SAAnd judging whether the climate condition of the target basin meets the climate condition of the outbreak of the glacier debris flow with extra large scale or not according to the two-dimensional space optimal segmentation hyperplane obtained in the step S33, specifically:
according to the accumulated temperature index lambda and the equivalent river basin ratio of the snow water of the target river basinSACalculating a determination factor of the catastrophe climateT D-year ：
T D-year = k 3 SA+k 4 λ
Wherein the content of the first and second substances,k 3 、k 4 is the temperature accumulation index lambda and the snow water equivalent basin ratioSAFitting coefficients of the optimal dividing lines of the constructed two-dimensional space;
setting a catastrophe climate threshold value according to a maximum geometric interval of a two-dimensional spaceT y-threshold ：
Wherein the content of the first and second substances,w、bdividing a plane parameter for the minimum vector distance of the two-dimensional space of the disaster occurrence sample and the non-occurrence sample;
judging a catastrophe climate decision factorT D-year And catastrophe climate thresholdT y-threshold If the magnitude relation of (1) is satisfiedT D-year ＞T y-threshold And judging that the climate conditions of the glacier debris flow outbreak in extra large scale are met.
The above-mentioned two-dimensional space minimum vector distance is solved by the following formula:
s35, calculating the average air temperature of the target basin debris flow formation area in about 30 daysT Ave30 And accumulated rainfallP Acc30 。
S36, calculating the average temperature of the catastrophe day near 30 days based on the disaster history sampleT Ave30 And accumulated rainfallP Acc30 Calculating the average temperature of the same period adjacent to the current year of the disaster and the year without the disasterT Ave30 And accumulated rainfallP Acc30 . The non-disaster period can be only one year or many years, and the disaster occurs in the first five years of the current year in the subsequent verification process.
S37, constructing average air temperatureT Ave30 And accumulated rainfallP Acc30 The data of the current year of disaster occurrence and the year adjacent to the current year of disaster occurrence and without disaster occurrence are projected to the two-dimensional space, an SVM (support vector machine) is utilized to solve an optimal segmentation hyperplane of the two-dimensional space, and the formula of the optimal segmentation hyperplane is as follows:
w T x i +y i +b=0
wherein the content of the first and second substances,w、bfor optimal segmentation of the hyperplane coefficients,x i for two-dimensional space disaster sample pointsxA set of axis coordinates is set for each of the axes,y i for two-dimensional space disaster sample pointsyAn axis coordinate set; mean air temperatureT Ave30 And accumulated rainfallP Acc30 And is andxyand may be arbitrary, during the subsequent verification process,xaxial coordinate of 30 days average temperatureT Ave30 ，yAxial coordinate of 30 days cumulative rainfallP Acc30 。
S38, average air temperature obtained based on step S35T Ave30 And accumulated rainfallP Acc30 And judging whether the meteorological conditions of the target basin meet the meteorological conditions of the outbreak of the glacier debris flow with the extra-large scale or not according to the two-dimensional space optimal segmentation hyperplane obtained in the step S37, specifically speaking:
according to the target basin average air temperatureT Ave30 And accumulated rainfallP Acc30 Calculating a catastrophe weather determination factorT D-day ：
T
D-day
= k
5
P
Acc30
+k
6
T
Ave30
Wherein the content of the first and second substances,k 5 、k 6 is the average air temperatureT Ave30 And accumulated rainfallP Acc30 Fitting coefficients of the optimal dividing lines of the constructed two-dimensional space;
setting a catastrophe meteorological threshold according to a maximum geometric interval of a two-dimensional spaceT d-threshold ：
Wherein the content of the first and second substances,w、bdividing a plane parameter for the minimum vector distance of the two-dimensional space of the disaster occurrence sample and the non-occurrence sample;
determining a catastrophe weather determination factorT D-day And a catastrophe meteorological thresholdT d-threshold If the magnitude relation of (1) is satisfiedT D-day ＞T d-threshold And judging that the extreme large scale glacier debris flow outbreak meteorological conditions are met.
The above-mentioned two-dimensional space minimum vector distance is solved by the following formula:
s4, alarming the disaster of the extra-large scale glacier debris flow when the events simultaneously meet the disaster weather determination condition and the disaster weather determination condition, and storing the sample data of the extra-large scale glacier debris flow in a warehouse to expand the sample for calculating and analyzing the next event, thereby further improving the accuracy of subsequent early warning.
In order to further verify the effectiveness of the extra-large scale glacier debris flow early warning method provided by the invention in the early warning of the disaster of the extra-large scale glacier debris flow in the high-altitude mountain area, verification is carried out by taking the extra-large glacier debris flow in the ancient rural gully of 30 days in 2005, the extra-large glacier debris flow in the imperial gully of 4 days in 9 months in 2007, and the extra-large glacier debris flow in the Mowa gully of 25 days in 7 months in 2010 as specific verification cases.
Verification example 1:
the ancient rural gully is located in the palong drainage basin on the Tibet plateau, the geographic coordinates are 29.92 degrees N and 95.44 degrees E, and sigma =0.65, M =0.96 and E =59.06 are obtained through calculation through optical remote sensing and topographic data.
And E is judged to be more than 59, and the flow field is a glacier debris flow field needing important monitoring.
The catastrophe day of the ancient rural ditches is 30 days 7 months in 2005, and the daily air temperature, rainfall and accumulated snow water equivalent of the optimized mud-rock flow forming area of the ancient rural ditches in the current year are calculated, so that the catastrophe day snow water equivalent index of the ancient rural ditches is SA =0.33, and lambda = 1.62.
Performing two-dimensional space regression statistics based on the equivalent index and the accumulated temperature index of snow water in the same period of the current year and the previous year of disaster of the existing disaster sample, and obtaining k through calculation by partitioning and solving the optimal two-dimensional space3=1、k4=3.18、Ty-threshold=5.46。
Substituting the calculated catastrophe current year snow water equivalent index SA =0.33 and the calculated temperature accumulation index lambda =1.62 into a formula
TD-year= SA+3.18λ
Calculating to obtain TD-year=5.48，TD-yearAnd if the weather condition is more than 5.46, the weather condition is judged to be met with the storm climate condition of the glacier debris flow with the extra large scale.
Average temperature T of 30 consecutive days before the same period based on the current day and five adjacent years of the existing disaster sampleAve30And accumulated rainfall PAcc30Performing two-dimensional space regression statistics, solving by optimal two-dimensional space segmentation, and calculating to obtain k5=1，k6=33.47，Td-threshold=518.02。
Calculating the average temperature T of the ancient village ditch in 2005 from 1 month to 7 months and 30 daysAve30And accumulating rainfall PAcc30To obtain TAve30=14.02℃、PAcc30=82.13mm, and then solve to get TD-day=551.38， TD-dayWhen the weather condition is more than 518.02, the weather condition of the ancient rural ditch of 30 days 7 and 7 months 2005 is judged to meet the weather condition of short duration of the outbreak of the glacier debris flow with extra large scale, and an alarm is given out.
Verification example 2:
the dragon ditch is located in a PanlongTing distribution area on the Tibet plateau, the geographic coordinates are 30.04 degrees N and 95.01 degrees E, and sigma =0.04, M =0.99 and E =60.26 are obtained through optical remote sensing and topographic data in a calculation mode.
And E is judged to be more than 59, and the flow field is a glacier debris flow field needing important monitoring.
The cataclysm day of the dragon ditch is 9, 4 and 2007, the day-by-day air temperature, rainfall and accumulated snow water equivalent after the optimization of the current year of the forming area of the mud-rock flow of the dragon ditch are calculated, and the cataclysm current year snow water equivalent index of the dragon ditch is SA =0.47 and lambda = 1.67.
Performing two-dimensional space regression statistics based on the equivalent index and the accumulated temperature index of snow water in the same period of the current year and the previous year of disaster of the existing disaster sample, and obtaining k through calculation by partitioning and solving the optimal two-dimensional space3=1、k4=3.04、Ty-threshold=5.31。
Substituting the calculated equivalent index SA =0.47 and the calculated accumulative temperature index lambda =1.67 of the catastrophe snow water of the current year into a formula
TD-year= SA+3.04λ
Calculating to obtain TD-year=5.55，TD-yearIf the weather condition is more than 5.31, the weather condition is judged to be in accordance with the storm climate condition of the glacier debris flow with the extra large scale.
Average temperature T of 30 consecutive days before the same period of the current day and five adjacent years based on the existing disaster sampleAve30And accumulated rainfall PAcc30Performing two-dimensional space regression statistics, solving by optimal two-dimensional space segmentation, and calculating to obtain k5=1，k6=31.19，Td-threshold=460.83。
Calculating average temperature T of the culture ditch in 2007 in the continuous 30 days from 8 months, 6 days to 9 months and 4 daysAve30And accumulating rainfall PAcc30To obtain TAve30=12.83℃、PAcc30=97.77mm, and then solve for TD-day=497.93， TD-dayWhen the weather condition is more than 460.83, the weather condition of the Japanese gutter at 9 month and 4 months in 2007 is judged to meet the weather condition of the short duration of the outbreak of the glacier debris flow with extra large scale, and an alarm is given out.
Verification example 3:
the Tianmo gully is located in the Panlongtibo drainage basin on the Tibet plateau, the geographic coordinates are 29.99 degrees N and 95.32 degrees E, and sigma =0.04, M =0.99 and E =60.26 are obtained through calculation through optical remote sensing and topographic data.
And E is judged to be more than 59, and the flow field is a glacier debris flow field needing important monitoring.
The cataclysm day of the Tianmo ditch is 7 and 25 days in 2010, and the daily temperature, rainfall and snow water accumulation equivalent of the Tianmo ditch debris flow forming area after the current year optimization are calculated to obtain the cataclysm day-by-day snow water equivalent index of the Tianmo ditch of SA =0.45 and lambda = 1.61.
Performing two-dimensional space regression statistics based on the equivalent index and the accumulated temperature index of snow water in the same period of the current year and the previous year of disaster of the existing disaster sample, and obtaining k through calculation by partitioning and solving the optimal two-dimensional space3=1、k4=3.38、Ty-threshold=5.62。
Substituting the calculated equivalent index SA =0.45 and the temperature accumulation index lambda =1.61 of the snow water in the catastrophe current year into a formula
TD-year= SA+3.38λ
Calculating to obtain TD-year=5.89，TD-yearAnd if the weather conditions are more than 5.62, judging that the weather conditions are met with the storm climate conditions of the glacier debris flow with the extra large scale.
Average temperature T of 30 consecutive days before the same period of the current day and five adjacent years based on the existing disaster sampleAve30And accumulated rainfall PAcc30Performing two-dimensional space regression statistics, solving by optimal two-dimensional space segmentation, and calculating to obtain k5=1，k6=30.89，Td-threshold=453.22。
Calculating the average temperature T of 30 consecutive days from 6 months, 25 days to 7 months, 25 days of Tianmo ditch 2010Ave30And accumulating rainfall PAcc30To obtain TAve30=14.31℃、PAcc30=108.23mm, and then solve for TD-day=550.26， TD-dayWhen the weather condition is more than 453.22, the weather condition of Mogou in 25 days of 7 months and 25 days in 2010 is judged to meet the weather condition of short duration of the outbreak of the glacier debris flow with extra large scale, and an alarm is given out.
Although the present invention has been described herein with reference to the preferred embodiments thereof, which are intended to be illustrative only and not to be limiting of the invention, it will be understood that numerous other modifications and embodiments can be devised by those skilled in the art that will fall within the spirit and scope of the principles of this disclosure.
Claims (15)
1. The early warning method for the glacier debris flow on the extra-large scale is characterized by comprising the following steps of:
s1, calculating material energy parameters of each glacial debris flow basin in the monitoring area range according to the longitudinal slope ratio of the main ditch of the glacial debris flow basin and loose material sources, and screening the glacial debris flow basin needing to be monitored in a key mode according to the material energy parameters; the method specifically comprises the following steps of S11-S15:
s11, interpreting and identifying the range of the loose object sources distributed in the flow field based on the optical remote sensing image, and calculating according to the identified rangeArea of loose sourceμ i The bulk source comprises a moraine and a paleo;
s12, extracting the range of the drainage basin and the height difference from the highest point of the channel forming area to the channel opening by using the digital elevation modelhAnd the horizontal distance from the highest point of the channel formation region to the trench openingl(ii) a Calculating the area of the drainage basin according to the range of the drainage basinArea basin Calculating the longitudinal slope gradient ratio of the main trench according to the height difference and the horizontal distances：
s=h/l×100%；
S13, calculating material energy parameters including main ditch longitudinal slope ratio reduction normalization indexσ i And main furrow loose source indexM i ：
Wherein the content of the first and second substances,s i for the current calculation of the main trench longitudinal slope gradient of the watershed,s j for the current calculation of the main ditch longitudinal slope gradient of the sub basin in the main basin where the basin is located,nfor the current calculation of the number of sub-domains within the parent domain to which the domain belongs,μ i to currently calculate the loose source area of the watershed,icalculating the serial number of the current basin;
s14, calculating the material energy value of the watershed according to the material energy parameterE i ：
E i = k 1 σ i +k 2 M i
Wherein the content of the first and second substances,k 1 、k 2 is a weighting coefficient;
s15, calculating the energy value of the materialE i The glacier debris flow basin which is larger than the preset energy condition threshold of the glacier debris flow material with the extra-large scale is judged as the glacier debris flow basin which needs to be monitored in a key way;
s2, respectively analyzing and calculating water source factors of the glacier debris flow basin monitored at the heavy point, wherein the water source factors comprise the air temperature, precipitation and snow water equivalent of a debris flow forming area;
s3, based on the result of the water source factor analysis and calculation in the step S2, carrying out catastrophe weather judgment by utilizing the extra-large scale glacier debris flow catastrophe weather judgment model, and carrying out catastrophe weather judgment by utilizing the extra-large scale glacier debris flow catastrophe weather judgment model; if the catastrophe climate judgment and the catastrophe weather judgment both meet the corresponding catastrophe climate judgment condition and catastrophe weather judgment condition, the early warning condition is met, otherwise, the early warning condition is not met;
and S4, carrying out debris flow disaster alarm on the glacier debris flow watershed meeting the early warning condition.
2. The extra-large scale glacier debris flow early warning method of claim 1, wherein in the step S2, the water source factor analysis and calculation are respectively performed on the heavily monitored glacier debris flow basin, and the method specifically comprises the following steps:
s21, performing regional air temperature interpolation on the target basin;
s22, local air temperature correction is carried out based on the regional air temperature interpolation and the air temperature observation data of the monitoring points;
s23, acquiring regional precipitation inversion data;
s24, local precipitation correction is carried out based on the regional precipitation inversion data and the rainfall observation data of the monitoring points;
s25, acquiring regional snow inversion data;
and S26, calculating the regional total snow water equivalent based on the regional snow inversion data.
3. The early warning method for the extra large scale glacier debris flow as claimed in claim 2,
in step S21, the performing the region air temperature interpolation on the target basin specifically includes:
carrying out regional air temperature interpolation on the target basin based on a thin-plate smooth spline interpolation method by utilizing daily air temperature observation data of an adjacent meteorological station of the target basin and topographic data of the target basin:
T i = f（x i ）+bT y i +e i
wherein, the first and the second end of the pipe are connected with each other,T i for meshes within a target stream domainiAs a result of the interpolation of the air temperature,f（x i ）is a gridx i B is a terrain covariate coefficient,y i is a gridx i Elevation value of e i Is a random error.
4. The early warning method for the extra large scale glacier debris flow as claimed in claim 2,
in step S22, the performing local air temperature correction based on the region air temperature interpolation and the monitored point air temperature observation data specifically includes:
s221, acquiring day-by-day air temperature observation data of the monitoring stations through air temperature monitoring equipment installed at each monitoring station of the target basint i And is connected with the grid to which the monitoring station belongsx i Result of air temperature interpolationT i Calculating difference to obtain single point temperature correction value of temperature interpolation and observation valueR Ti ；
S222, temperature correction value based on each monitored station in target flow domainR Ti Constructing a Thiessen polygon, performing spatial interpolation, and generating local air temperature correction dataR T ；
S223, the regional air temperature interpolation result and the local air temperature correction dataR T Adding after unifying the resolution, calculating to obtain local temperature optimization dataT R 。
5. The early warning method for the extra large scale glacier debris flow as claimed in claim 2,
in step S23, regional precipitation inversion data are obtained based on global precipitation remote sensing data GPM or TRMMP。
6. The early warning method for the extra large scale glacier debris flow as claimed in claim 2,
in step S24, the local precipitation correction based on the regional precipitation inversion data specifically includes:
s241, acquiring day-by-day rainfall data of monitoring points through rainfall monitoring equipment installed at each monitoring point of the target drainage basinp i Extracting regional precipitation dataPGrid to which middle monitoring point belongsx i Precipitation inversion dataP i Through and day-by-day rainfall datap i Obtaining local rainfall correction value by differenceR Pi ；
S242, rainfall correction data obtained based on monitoring stations of target basinR Pi Building Thiessen polygons and performing spatial interpolation to generate local precipitation correction dataR P ；
S243, inverting data of regional precipitationPAnd local precipitation correction dataR P Adding after unifying the resolution, and calculating to obtain local precipitation optimization dataP R 。
7. The pre-warning method for the extra-large scale glacier debris flow as claimed in claim 2, characterized in that,
in step S25, the acquiring of regional snow inversion data specifically includes:
obtaining the snow cover area of the debris flow forming area of the target watershed through the interpretation of the MODIS day-by-day snow dataArea snow And obtaining the snow thickness of the snow accumulation area by using AMSR-E microwave snow depth dataDepth snow 。
8. The pre-warning method for the extra-large scale glacier debris flow as claimed in claim 2, characterized in that,
in step S26, the calculating the total snow water equivalent of the area based on the inversion data of the area snow specifically includes:
first, the equivalent of snow water in unit area is calculatedSWE：
Wherein the content of the first and second substances,Depth s_k is a firstkThe depth of the accumulated snow in the day,ρ w which is indicative of the density of the water,ρ 0 the density of the fresh accumulated snow is the density,SD k is as followskThe depth of the snow in the day is,ρ s_k is the firstkThe density of the snow in the day is,nindicating the number of days from the current day of target basin monitoring to the start day of its adjacent winter half year.
9. The extra-large scale glacier debris flow early warning method as claimed in claim 1,
in the step S3, the catastrophe climate determination model for the extra-large scale glacier debris flow is as follows:
s31, calculating the temperature accumulation index lambda and the equivalent river basin ratio of the snow water in the debris flow forming area in the time interval from the target river basin monitoring day to the start day of the adjacent winter half yearSA；
S32, calculating the temperature accumulation index lambda and the snow water equivalent basin ratio of the disaster occurring year, the period adjacent to the disaster occurring year and the period without the disaster occurring year based on the disaster history sampleSATaking the beginning date of the winter half year adjacent to the disaster occurrence date as a starting date, wherein the time interval of adjacent years is the interval from the starting date of the current Gregorian year to the starting date of the previous Gregorian year, and the time interval of the disaster occurrence current year is the interval from the starting date to the disaster occurrence current day;
s33, constructing equivalent river basin ratio of snow waterSAA two-dimensional space of temperature accumulation index lambda and the disasterProjecting data of the current year of disaster occurrence and the year adjacent to the current year of disaster occurrence and without the disaster to a two-dimensional space, and performing regression analysis;
s34, obtaining the temperature accumulation index lambda and the snow water equivalent basin ratio based on the step S31SAAnd judging whether the climate condition of the target basin meets the climate condition of the outbreak of the extra-large scale glacier debris flow or not according to the analysis result obtained in the step S33.
10. The early warning method for the extra large scale glacier debris flow as claimed in claim 9,
the calculation method of the accumulated temperature index lambda of the debris flow formation area comprises the following steps:
wherein the content of the first and second substances,ATforming effective accumulated temperature of a region for the debris flow, and optimizing data by daily temperature in a specified time intervalT R Accumulating to obtain, if the temperature is positive temperature, accumulating, otherwise, not accumulating;Dthe number of days of positive temperature accumulated in a specified time interval;kis a regression fitting coefficient;
the designated time interval is the time interval designated in step S31 and step S32.
11. The early warning method for the extra large scale glacier debris flow as claimed in claim 9,
in step S31, the snow-water equivalent watershed ratio of the debris flow formation areaSAThe calculation method comprises the following steps:
wherein the content of the first and second substances,SnowMass accum for the cumulative equivalent of snow water in a given time interval, by the equivalent of snow water per unit areaSWEThe accumulated calculation is carried out;Area snow forming accumulated snow coverage area for debris flow forming area;daysrepresenting the number of valid days within a specified time interval; ΔSWEThe difference between the equivalent quantity of the snow water of the next day and the equivalent quantity of the snow water of the previous day is counted into the equivalent quantity of the accumulated snow water if the difference is a positive number, and the accumulated snow water is not counted if the difference is a negative number, which indicates that no newly added snow quantity exists; the designated time intervals are the time intervals designated in step S31 and step S32.
12. The extra-large scale glacier debris flow early warning method of claim 9, wherein the regression analysis of the step S33 is to solve an optimal segmentation hyperplane of a two-dimensional space; in the step S34, the temperature accumulation index λ and the snow water equivalent flow area ratio obtained in the step S31 are used as the basisSAAccording to the two-dimensional space optimal segmentation hyperplane obtained in the step S33, whether the climate condition of the target basin meets the climate condition of the outbreak of the glacier debris flow with the extra-large scale is judged, and the method specifically comprises the following steps:
according to the accumulated temperature index lambda and the snow water equivalent basin ratio of the target basinSACalculating a catastrophe climate decision factorT D-year ：
T D-year = k 3 SA+k 4 λ
Wherein the content of the first and second substances,k 3 、k 4 is the temperature accumulation index lambda and the snow water equivalent basin ratioSAFitting coefficients of the optimal dividing lines of the constructed two-dimensional space;
setting a catastrophe climate threshold value according to a maximum geometric interval of a two-dimensional spaceT y-threshold ：
Wherein, the first and the second end of the pipe are connected with each other,w、bdividing a plane parameter for the minimum vector distance of the two-dimensional space of the disaster occurrence sample and the non-occurrence sample;
judging a catastrophe climate decision factorT D-year And catastrophe climate thresholdT y-threshold If the magnitude relation of (1) is satisfiedT D-year ＞T y-threshold And judging that the climate conditions of the glacier debris flow outbreak in extra large scale are met.
13. The early warning method for extra large scale glacier debris flow as claimed in any one of claims 1 or 9,
in the step S3, the catastrophe meteorological determination model for the extra-large scale glacier debris flow is as follows:
s35, calculating the average air temperature of the target watershed debris flow forming area in the last 30 daysT Ave30 And accumulated rainfallP Acc30 ；
S36, calculating the average temperature of the catastrophe day near 30 days based on the disaster history sampleT Ave30 And accumulated rainfallP Acc30 Calculating the average temperature of the same period adjacent to the current year of disaster occurrence and the year of no disaster occurrenceT Ave30 And accumulated rainfallP Acc30 ；
S37, constructing average air temperatureT Ave30 And accumulated rainfallP Acc30 The data of the current year of the disaster and the data of the year adjacent to the current year of the disaster without the disaster are projected to the two-dimensional space, and regression analysis is carried out;
s38, average air temperature obtained based on step S35T Ave30 And accumulated rainfallP Acc30 And judging whether the meteorological conditions of the target basin accord with the meteorological conditions of the outbreak of the extra-large scale glacier debris flow or not according to the analysis result obtained in the step S37.
14. The extra large scale glacier debris flow early warning method of claim 13,
in step S35, the average temperature for approximately 30 daysT Ave30 And accumulated rainfallP Acc30 The calculation method comprises the following steps:
wherein the content of the first and second substances,T Ri andP Ri respectively a debris flow forming areaiThe daily optimized air temperature value and the optimized rainfall value.
15. The extra large scale glacier debris flow early warning method of claim 13,
the regression analysis in the step S37 is to solve the optimal segmentation hyperplane of the two-dimensional space; in step S38, the average air temperature is obtained based on the average air temperature obtained in step S35T Ave30 And accumulated rainfallP Acc30 And judging whether the meteorological conditions of the target basin meet the meteorological conditions of the outbreak of the glacier debris flow with the extra-large scale according to the two-dimensional space optimal segmentation hyperplane obtained in the step S37, and the method specifically comprises the following steps:
according to the target basin average air temperatureT Ave30 And accumulated rainfallP Acc30 Calculating a catastrophe weather determination factorT D-day ：
T
D-day
= k
5
P
Acc30
+k
6
T
Ave30
Wherein the content of the first and second substances,k 5 、k 6 is the average air temperatureT Ave30 And accumulated rainfallP Acc30 Fitting coefficients of the optimal dividing lines of the constructed two-dimensional space;
setting a catastrophe meteorological threshold according to a maximum geometric interval of a two-dimensional spaceT d-threshold ：
Wherein the content of the first and second substances,w、bdividing a plane parameter for the minimum vector distance of the two-dimensional space of the disaster occurrence sample and the non-occurrence sample;
determining a catastrophe weather determination factorT D-day And a catastrophe meteorological thresholdT d-threshold If the magnitude relation of (1) is satisfiedT D-day ＞T d-threshold And judging that the extreme large scale glacier debris flow outbreak meteorological conditions are met.
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