CN102646219A - Method for pre-warning snow disaster in pasturing area - Google Patents

Abstract

The invention relates to a method for pre-warning snow disaster in a pasturing area. The method comprises the steps of: collecting and analyzing data and information of disaster inducing capacity of accumulated snow in the pasturing area, disaster resistance in the pasturing area, livestock supporting body and weather forecast; constructing a pre-warning index system and a pre-warning diagnosis model for pre-warning snow disaster; constructing a snow disaster pre-warning grading model and a snow disaster pre-warning grading standard by combining the weather forecast; carrying out pre-warning grading on the snow disaster; checking and correcting the snow disaster pre-warning grading model and the snow disaster pre-warning grading standard; and integrating the established snow disaster pre-warning grading model and standard with a snow disaster danger level model and standard into a multi-source information integration pre-warning system, and issuing pre-warning information, risk management and pre-warning decision plans through the multi-source information integration pre-warning system. The method realizes a grid unit-based spatial snow disaster distribution map and a county region unit-based snow disaster danger degree division map, and also realizes dynamic pre-warning of dynamic spatialization.

Description

The method for early warning of pastoral area snow disaster

Technical field

The present invention relates to the method for early warning of a kind of pastoral area snow disaster.

Background technology

Snow disaster is one of main disaster in winter-spring season pastoral area.When the accumulated snow cladding thickness acquires a certain degree; Bury the grassland, suspend traffic, there's a sudden fall in temperature; Cause the domestic animal difficulty of searching for food; The feed underfeed causes large quantities of domestic animals because of hungry, cold dead disastrous loss, is having a strong impact on the pastoral area grassland agriculture expanding economy and the herdsman masses' the security of the lives and property.Carry out the early warning of pastoral area snow disaster, to strengthening the defence capability of pastoral area snow disaster, the loss that the minimizing snow disaster causes has important scientific meaning and use value.

Research to the snow disaster method for early warning mainly is from aspects such as meteorological and topography and geomorphologies both at home and abroad, and employing is flowed or blow over and cover completely index and carried out early warning, thinks as long as the degree of depth and the coverage rate of snowfall acquire a certain degree, and has just formed snow disaster.But the prerequisite that the pastoral area snow disaster forms is incomplete the causing of the under-supply and warming facility of fodder grass, if sufficient fodder grass deposit and warming facility are arranged, is that accumulated snow is very serious, also can not cause snow disaster.The RSR method for early warning is taken all factors into consideration the relation that pastoral area strength of combatting natural disaster, domestic animal hazard-affected body and accumulated snow cause calamity power, and at first according to pastoral area strength of combatting natural disaster level, whether diagnosis snow disaster takes place.If the pastoral area strength of combatting natural disaster is not enough, cause calamity power less than accumulated snow, snow disaster will take place.Therefore, with the hazard rating standard pastoral area snow disaster is divided into different advanced warning grades and hazard rating, so that formulate the prediction scheme of fighting calamities and providing relief accordingly according to early warning.

Summary of the invention

The method for early warning that the purpose of this invention is to provide a kind of pastoral area snow disaster.The present invention utilizes 3S technology (remote sensing, GIS-Geographic Information System and GPS) combined ground monitoring materials and medium-term and long-term weather forecast; Strength of combatting natural disaster, domestic animal hazard-affected body and snowfall cause calamity power (two power one RSA) aspect from the pastoral area; Pastoral area snow disaster diagnostic model, snow disaster early warning hierarchy model and snow disaster classification standard have been made up; The pastoral area snow disaster is carried out early warning, can realize based on the space snow disaster distribution plan of grid unit with based on the snow disaster harm zoning map of unit, territory, county.

The object of the invention is realized through following technical scheme: the method for early warning of a kind of pastoral area snow disaster comprises the steps:

1) pastoral area accumulated snow is caused calamity power, pastoral area strength of combatting natural disaster, livestock supporting body and weather forecast and carry out data and Data acquisition, and analysis;

2), make up warning index system and early warning diagnostic model snow disaster is carried out early warning with the data that in the step 1) accumulated snow caused calamity power, pastoral area strength of combatting natural disaster, livestock supporting body Collection and analysis;

3) combine weather forecast, make up snow disaster early warning hierarchy model and standard, snow disaster is carried out the early warning classification;

4) verify snow disaster early warning hierarchy model and standard, and it is revised;

5) combine the livestock anticipated mortality, make up snow disaster hazard rating model and standard;

6) with step 4) and 5) the snow disaster early warning hierarchy model set up and standard and snow disaster hazard rating model and regular set become the integrated early warning system of multi-source information, and issue preparatory information, risk management and early warning decision prediction scheme through the integrated early warning system of multi-source information.

Further, after described step 3), also comprise the step of setting up the hazard evaluation model.

Further, in described step 2) described in the early warning diagnostic model that makes up be:

$S_{\mathrm{ij}}=\underset{j=1}{\overset{n}{\mathrm{\Σ}}}\left(X_{\mathrm{ij}}{W}_{\mathrm{ij}}\right)$

$R_{\mathrm{ij}}=\underset{j=1}{\overset{n}{\mathrm{\Σ}}}{Z}_{\mathrm{ij}}\×w_{\mathrm{ij}}\×p_{\mathrm{ij}}$

${\mathrm{SD}}_{\mathrm{ij}}=\underset{j=1}{\overset{n}{\mathrm{\Π}}}{S}_{\mathrm{ij}}-\underset{j=1}{\overset{n}{\mathrm{\Π}}}{R}_{\mathrm{ij}}$

Work as SD _Ij＞0 o'clock, no snow disaster;

Work as SD _Ij, snow disaster is arranged at≤0 o'clock;

In the formula: S _IjBe the preceding pastoral area of calamity strength of combatting natural disaster index; X _IjFor combating a natural disaster the level of factor quantized value; W _IjFor combating a natural disaster factor single index weight; R _IjFor the accumulated snow calamity causes calamity power index; Z _IjFor causing calamity level of factor quantized value; w _IjFor causing calamity factor single index weight; p _IjProbability for period of history month generation snow disaster.SD _IjBe snow disaster early warning diagnostic index.

Further, at the snow disaster early warning hierarchy model that makes up described in the described step 3) be:

${\mathrm{SW}}_{\mathrm{ij}}=1-\frac{S_{\mathrm{ij}}}{R_{\mathrm{ij}}}$

In the formula: SW _IjBe snow disaster early warning grading index; S _IjBe the preceding pastoral area of calamity strength of combatting natural disaster index; R _IjFor the accumulated snow calamity causes calamity power index.Further, the hazard evaluation model of described structure is:

${\mathrm{SH}}_{\mathrm{ij}}={\mathrm{SW}}_{\mathrm{ij}}\underset{j=1}{\overset{n}{\mathrm{\Σ}}}\left(D_{\mathrm{ij}}{p}_{\mathrm{ij}}\right)\×100\%$

In the formula: SH _IjBe certain month snow disaster harm expected loss rate; D _IjDomestic animal mortality ratio for the different brackets snow disaster; p _IjThe weather forecast probability of snow disaster took place in following certain month; SW _IjBe snow disaster early warning grading index.

Further, described step 1) specifically comprises the steps:

(1) confirms the snow disaster zone;

(2) data and Data acquisition: accumulated snow is caused calamity power, pastoral area strength of combatting natural disaster, livestock supporting body and weather forecast and pregnant calamity environmental information is carried out data aggregation;

(3) accumulated snow of collecting in the step (2) is caused calamity power, pastoral area strength of combatting natural disaster and livestock supporting body data and analyze, to make up the snow disaster pre-alarming system;

(4) use the data after the analysis in the step (3), make up snow disaster warning index system, early warning diagnostic model, early warning hierarchy model and standard and snow disaster hazard rating model and standard;

(5) verify snow disaster warning index, model and standard, and it is revised.

Further, it is through ground monitoring and statistical data that described accumulated snow causes calamity power and pastoral area strength of combatting natural disaster data and Data acquisition,, and combining environmental mitigation wind and cloud satellite and satellite MODIS data are to the remote sensing monitoring of accumulated snow, meadow, traffic settlement;

Said data aggregation to accumulated snow comprises: snow depth, accumulated snow coverage rate and low temperature continuous days;

Said data aggregation to the meadow comprises: meadow output, meadow availability, herbage height, herbage deposit, livestock shed facility and herdsman's economic situation;

Said data aggregation to the traffic settlement comprises: pastoral area traffic communication situation and settlement distribute.

Further, livestock supporting body data and Data acquisition, are through being that the releve of elementary cell carries out meteorology, herdsman livestock, socioeconomic ground monitoring with the county with herding the family;

Said data aggregation to meteorology comprises: precipitation, temperature, wind-force and low temperature continuous days;

Said data aggregation to the herdsman livestock comprises: herdsman and livestock body condition, structure and quantity;

Said socioeconomic data aggregation is comprised: forage reserves, livestock shed, house, medical treatment and herdsman's income.

Further, preparatory information, risk management and the early warning decision prediction scheme of the issue of the integrated early warning system of described multi-source information comprise that snow disaster endangers zoning map pastoral area snow disaster advanced warning grade figure, pastoral area strength of combatting natural disaster evaluation map and provides and combat a natural disaster the prediction scheme of taking precautions against natural calamities.

The integrated early warning system of described multi-source information is with step 4) and 5) snow disaster early warning hierarchy model and standard and the snow disaster hazard rating model and standard several data set up be stored in the spatial database, and pass through SQL Server database software and manage; Also use service object's manager that data are analyzed, and through Arc Catalo software administration; Simultaneously; Through Web server snow disaster harm zoning module, snow disaster advanced warning grade module, pastoral area strength of combatting natural disaster evaluation module and these 4 the module integrated comprehensives of prediction scheme module of combating a natural disaster to take precautions against natural calamities are analyzed and issue; It utilizes composition, structure, function and the operation method of Arc G IS Server platform; The integrated early warning system of multi-source information is supported under the distributed environment realizes geodata management, drawing and spatial analysis, realized dynamic issue and the space querying of loading, raster data and vector data of the Map Services of pastoral area snow disaster early warning.

Advantage of the present invention is: utilize 3S technology (remote sensing, GIS-Geographic Information System and GPS) combined ground monitoring materials and medium-term and long-term weather forecast; Strength of combatting natural disaster, domestic animal hazard-affected body and snowfall cause calamity power (two power one RSA) aspect from the pastoral area; Pastoral area snow disaster diagnostic model, snow disaster early warning hierarchy model and snow disaster classification standard have been made up; The pastoral area snow disaster is carried out early warning, can realize based on the space snow disaster distribution plan of grid unit with based on the snow disaster harm zoning map of unit, territory, county.Can see intuitively that snow disaster is distributed in those zones, its extent of injury has much." the two power one " of pastoral area snow disaster be method for early warning (RSA), and can be fights calamities and provides relief provides scientific basis.This method thinking is unique, and the early warning precision is high, is in the leading level in the world, has filled up the blank of pastoral area snow disaster method for early warning.

The invention has the beneficial effects as follows:

1) the RSR method for early warning is the interaction relationship that causes calamity power according to pastoral area strength of combatting natural disaster, domestic animal hazard-affected body and accumulated snow, and the two is the acting force mutation analysis of carrier to livestock to cause calamity power with pastoral area strength of combatting natural disaster and accumulated snow, and whether the diagnosis snow disaster takes place.Promptly when the pastoral area strength of combatting natural disaster causes calamity power greater than accumulated snow, the animal husbandry snow disaster can not take place, when having only the pastoral area strength of combatting natural disaster to cause calamity power less than accumulated snow, just the animal husbandry snow disaster can take place.

2) the RSR method for early warning has made up snow disaster early warning diagnostic model, snow disaster hierarchy model and the grade scale that causes calamity power based on pastoral area strength of combatting natural disaster, domestic animal hazard-affected body and accumulated snow.

3) realized based on the space snow disaster distribution plan of grid unit with based on the snow disaster extent of injury zoning map of unit, territory, county

4) realized the dynamic early warning of dynamic spaceization.

The principle of this method is unique, and thinking is novel, and the precision of model is high, and early warning flow process and technology path are reasonable.

Description of drawings:

Practical implementation of the present invention combines accompanying drawing further to set forth.

Fig. 1 is a pastoral area snow disaster early warning principle;

Fig. 2 is pastoral area snow disaster early warning overall workflow figure;

Fig. 3 is pastoral area snow disaster warning index system figure.

Embodiment

Below in conjunction with accompanying drawing principle of the present invention and characteristic are described, institute gives an actual example and only is used to explain the present invention, is not to be used to limit scope of the present invention.

Embodiment 1: like Fig. 1, Fig. 2, Fig. 3, the method for early warning of a kind of pastoral area snow disaster comprises the steps:

1) accumulated snow is caused calamity power, pastoral area strength of combatting natural disaster, livestock supporting body and weather forecast and carry out data and Data acquisition, and analysis;

Wherein, it is through ground monitoring and statistical data that described accumulated snow causes calamity power and pastoral area strength of combatting natural disaster data and Data acquisition,, and combining environmental mitigation wind and cloud satellite and satellite MODIS data are to the remote sensing monitoring of accumulated snow, meadow, traffic settlement;

Said data aggregation to accumulated snow comprises: snow depth, accumulated snow coverage rate and low temperature continuous days;

Said data aggregation to the meadow comprises: meadow output, meadow availability, herbage height, herbage deposit, livestock shed facility and herdsman's economic situation;

Said data aggregation to the settlement comprises: pastoral area traffic communication situation and settlement distribute.

Livestock supporting body data and Data acquisition, are through being that the releve of elementary cell carries out meteorology, herdsman livestock, socioeconomic ground monitoring with the county with herding the family;

Said data aggregation to meteorology comprises: precipitation, temperature, wind-force and low temperature continuous days;

Said data aggregation to the herdsman livestock comprises: herdsman and livestock body condition, structure and quantity;

Said socioeconomic data aggregation is comprised: forage reserves, livestock shed, house, medical treatment and herdsman's income.

2), make up warning index system and early warning diagnostic model snow disaster is carried out early warning with the data that in the step 1) accumulated snow caused calamity power, pastoral area strength of combatting natural disaster, livestock supporting body Collection and analysis;

Early warning diagnostic model at described structure is:

$S_{\mathrm{ij}}=\underset{j=1}{\overset{n}{\mathrm{\Σ}}}\left(X_{\mathrm{ij}}{W}_{\mathrm{ij}}\right)$

$R_{\mathrm{ij}}=\underset{j=1}{\overset{n}{\mathrm{\Σ}}}{Z}_{\mathrm{ij}}\×w_{\mathrm{ij}}\×p_{\mathrm{ij}}$

${\mathrm{SD}}_{\mathrm{ij}}=\underset{j=1}{\overset{n}{\mathrm{\Π}}}{S}_{\mathrm{ij}}-\underset{j=1}{\overset{n}{\mathrm{\Π}}}{R}_{\mathrm{ij}}$

Work as SD _Ij＞0 o'clock, no snow disaster;

Work as SD _Ij, snow disaster is arranged at≤0 o'clock;

In the formula: S _IjBe the preceding pastoral area of calamity strength of combatting natural disaster index; X _IjFor combating a natural disaster the level of factor quantized value; W _IjFor combating a natural disaster factor single index weight; R _IjFor the accumulated snow calamity causes calamity power index; Z _IjFor causing calamity level of factor quantized value; w _IjFor causing calamity factor single index weight; p _IjProbability for period of history month generation snow disaster.SD _IjBe snow disaster early warning diagnostic index.

3) combine weather forecast, make up snow disaster early warning hierarchy model and standard, snow disaster is carried out the early warning classification;

Snow disaster early warning hierarchy model at described structure is:

${\mathrm{SW}}_{\mathrm{ij}}=1-\frac{S_{\mathrm{ij}}}{R_{\mathrm{ij}}}$

In the formula: SW _IjBe snow disaster early warning grading index; S _IjBe the preceding pastoral area of calamity strength of combatting natural disaster index; R _IjFor the accumulated snow calamity causes calamity power index.

4) set up the hazard evaluation model;

The hazard evaluation model of described structure is:

${\mathrm{SH}}_{\mathrm{ij}}={\mathrm{SW}}_{\mathrm{ij}}\underset{j=1}{\overset{n}{\mathrm{\Σ}}}\left(D_{\mathrm{ij}}{p}_{\mathrm{ij}}\right)\×100\%$

In the formula: SH _IjBe certain month snow disaster harm expected loss rate; D _IjDomestic animal mortality ratio for the different brackets snow disaster; p _IjThe weather forecast probability of snow disaster took place in following certain month; SW _IjBe snow disaster early warning grading index.

5) verify snow disaster early warning hierarchy model and standard, and it is revised;

6) combine the livestock anticipated mortality, make up snow disaster hazard rating model and standard;

7) with step 5) and 6) the snow disaster early warning hierarchy model set up and standard and snow disaster hazard rating model and regular set become the integrated early warning system of multi-source information, and issue preparatory information, risk management and early warning decision prediction scheme through the delivery system of the integrated early warning system of multi-source information.Preparatory information, risk management and the early warning decision prediction scheme of the integrated early warning system of described multi-source information issue comprises that snow disaster endangers zoning map pastoral area snow disaster advanced warning grade figure, pastoral area strength of combatting natural disaster evaluation map and provides and combat a natural disaster the prediction scheme of taking precautions against natural calamities.

Wherein, described step 1) specifically comprises the steps:

(1) confirms the snow disaster zone;

(2) data and Data acquisition: accumulated snow is caused calamity power, pastoral area strength of combatting natural disaster, livestock supporting body and weather forecast and pregnant calamity environmental information is carried out data aggregation;

(3) accumulated snow of collecting in the step (2) is caused calamity power, pastoral area strength of combatting natural disaster and livestock supporting body data and analyze, to make up the snow disaster pre-alarming system;

(4) use the data after the analysis in the step (3), make up snow disaster warning index system, early warning diagnostic model, early warning hierarchy model and standard and snow disaster hazard rating model and standard;

(5) verify snow disaster warning index, model and standard, and it is revised.

Concrete step is:

101. confirm the snow disaster generation area;

102. utilize environment mitigation wind and cloud satellite; Combined ground monitoring and historical statistics data, the indexs of correlation such as accumulated snow, meadow, traffic settlement and meteorology, herdsman livestock, social economy that the accumulated snow of snow disaster generating region caused calamity power, pastoral area strength of combatting natural disaster and livestock supporting body are monitored and are analyzed;

103. utilize the data after step 102 monitoring and the analysis, make up pastoral area snow disaster warning index system;

104. further make up pastoral area snow disaster early warning diagnostic model;

105. further make up pastoral area snow disaster hierarchy model and standard;

106. further make up pastoral area snow disaster hazard rating evaluation model and standard;

107. utilize the snow disaster diagnostic model, whether the pastoral area snow disaster is taken place judge, the situation that snow disaster possibly take place is carried out early warning;

108. utilize early warning hierarchy model and sighting target accurate, the snow disaster of snow disaster generating region carried out early warning;

109. in conjunction with weather forecast, warning index system and model and standard carried out proof analysis and checking after, it is revised;

110. in conjunction with the livestock anticipated mortality, utilize snow disaster hazard rating model and standard, the snow disaster extent of injury carried out early warning;

111. utilize the 3S technology; Set up database and module; Be integrated into the integrated early warning system of multi-source information; Dynamically issue pastoral area snow disaster early warning information, risk management and early warning decision prediction scheme, (comprising snow disaster advanced warning grade figure, snow disaster harm zoning map, pastoral area strength of combatting natural disaster evaluation map and risk management and early warning decision prediction scheme).

Application examples: application this method is carried out early warning to the snow disaster in pastoral area, Zang Bei Nagqu in Dec, 2010.

(1) snow disaster diagnosis:

$S_{\mathrm{ij}}=\underset{j=1}{\overset{n}{\mathrm{\Σ}}}\left(X_{\mathrm{ij}}{W}_{\mathrm{ij}}\right)=0.624$

$R_{\mathrm{ij}}=\underset{j=1}{\overset{n}{\mathrm{\Σ}}}{Z}_{\mathrm{ij}}\×w_{\mathrm{ij}}\×p_{\mathrm{ij}}=0.875$

${\mathrm{SD}}_{\mathrm{ij}}=\underset{j=1}{\overset{n}{\mathrm{\Π}}}{S}_{\mathrm{ij}}-\underset{j=1}{\overset{n}{\mathrm{\Π}}}{R}_{\mathrm{ij}}=0.624-0.875=-0.251$

Snow disaster takes place in SDij≤0.

(2) snow disaster early warning classification:

${\mathrm{SW}}_{\mathrm{ij}}=1-\frac{S_{\mathrm{ij}}}{R_{\mathrm{ij}}}=1-0.624/0.875=0.287$

With the contrast of pastoral area snow disaster grade scale, belong to the moderate snow disaster.

Through investigation and analysis to 25 snow disaster monitoring points, pastoral area, Zang Bei Nagqu,

(3) hazard evaluation

${\mathrm{SH}}_{\mathrm{ij}}={\mathrm{SW}}_{\mathrm{ij}}\underset{j=1}{\overset{n}{\mathrm{\Σ}}}\left(D_{\mathrm{ij}}{p}_{\mathrm{ij}}\right)\×100\%=61.13\%$

The snow disaster extent of injury is a moderate.

According to the checking of 15 the snow disaster points for investigation in Zang Bei Nagqu, the precision of snow disaster early warning and hazard evaluation model reaches 89.21% and 65.37%.

The above is merely preferred embodiment of the present invention, and is in order to restriction the present invention, not all within spirit of the present invention and principle, any modification of being done, is equal to replacement, improvement etc., all should be included within protection scope of the present invention.

Claims (9)

1. the method for early warning of a pastoral area snow disaster, its characteristic comprises the steps:

1) pastoral area accumulated snow is caused calamity power, pastoral area strength of combatting natural disaster, livestock supporting body and weather forecast and carry out data and Data acquisition, and analysis;

2), make up warning index system and early warning diagnostic model snow disaster is carried out early warning with the data that in the step 1) accumulated snow caused calamity power, pastoral area strength of combatting natural disaster, livestock supporting body Collection and analysis;

3) combine weather forecast, make up snow disaster early warning hierarchy model and standard, snow disaster is carried out the early warning classification;

4) verify snow disaster early warning hierarchy model and standard, and it is revised;

5) combine the livestock anticipated mortality, make up snow disaster hazard rating model and standard;

6) with step 4) and 5) the snow disaster early warning hierarchy model set up and standard and snow disaster hazard rating model and regular set become the integrated early warning system of multi-source information, and issue preparatory information, risk management and early warning decision prediction scheme through the integrated early warning system of multi-source information.

2. the method for early warning of pastoral area as claimed in claim 1 snow disaster is characterized in that: after described step 3), also comprise the step of setting up the hazard evaluation model.

3. the method for early warning of pastoral area as claimed in claim 1 snow disaster is characterized in that: in described step 2) described in the early warning diagnostic model that makes up be:

$S_{\mathrm{ij}}=\underset{j=1}{\overset{n}{\mathrm{\Σ}}}\left(X_{\mathrm{ij}}{W}_{\mathrm{ij}}\right)$

$R_{\mathrm{ij}}=\underset{j=1}{\overset{n}{\mathrm{\Σ}}}{Z}_{\mathrm{ij}}\×w_{\mathrm{ij}}\×p_{\mathrm{ij}}$

${\mathrm{SD}}_{\mathrm{ij}}=\underset{j=1}{\overset{n}{\mathrm{\Π}}}{S}_{\mathrm{ij}}-\underset{j=1}{\overset{n}{\mathrm{\Π}}}{R}_{\mathrm{ij}}$

Work as SD _Ij＞0 o'clock, no snow disaster;

Work as SD _Ij, snow disaster is arranged at≤0 o'clock;

In the formula: S _IjBe the preceding pastoral area of calamity strength of combatting natural disaster index; X _IjFor combating a natural disaster the level of factor quantized value; W _IjFor combating a natural disaster factor single index weight; R _IjFor the accumulated snow calamity causes calamity power index; Z _IjFor causing calamity level of factor quantized value; w _IjFor causing calamity factor single index weight; p _IjProbability for period of history month generation snow disaster.SD _IjBe snow disaster early warning diagnostic index.

4. the method for early warning of pastoral area as claimed in claim 1 snow disaster is characterized in that: the snow disaster early warning hierarchy model making up described in the described step 3) is:

${\mathrm{SW}}_{\mathrm{ij}}=1-\frac{S_{\mathrm{ij}}}{R_{\mathrm{ij}}}$

In the formula: SW _IjBe snow disaster early warning grading index; S _IjBe the preceding pastoral area of calamity strength of combatting natural disaster index; R _IjFor the accumulated snow calamity causes calamity power index.

5. the method for early warning of pastoral area as claimed in claim 2 snow disaster is characterized in that: the hazard evaluation model of described structure is:

${\mathrm{SH}}_{\mathrm{ij}}={\mathrm{SW}}_{\mathrm{ij}}\underset{j=1}{\overset{n}{\mathrm{\Σ}}}\left(D_{\mathrm{ij}}{p}_{\mathrm{ij}}\right)\×100\%$

In the formula: SH _IjBe certain month snow disaster harm expected loss rate; D _IjDomestic animal mortality ratio for the different brackets snow disaster; p _IjThe weather forecast probability of snow disaster took place in following certain month; SW _IjBe snow disaster early warning grading index.

6. like the method for early warning of the arbitrary described pastoral area of claim 1 to 5 snow disaster, it is characterized in that: described step 1) specifically comprises the steps:

(1) confirms the snow disaster zone;

(2) data and Data acquisition: accumulated snow is caused calamity power, pastoral area strength of combatting natural disaster, livestock supporting body and weather forecast and pregnant calamity environmental information is carried out data aggregation;

(3) accumulated snow of collecting in the step (2) is caused calamity power, pastoral area strength of combatting natural disaster and livestock supporting body data and analyze, to make up the snow disaster pre-alarming system;

(4) use the data after the analysis in the step (3), make up snow disaster warning index system, early warning diagnostic model, early warning hierarchy model and standard and snow disaster hazard rating model and standard;

(5) verify snow disaster warning index, model and standard, and it is revised.

7. the method for early warning of pastoral area as claimed in claim 6 snow disaster; It is characterized in that: it is through ground monitoring and statistical data that described accumulated snow causes calamity power and pastoral area strength of combatting natural disaster data and Data acquisition,, and combining environmental mitigation wind and cloud satellite and satellite MODIS data are to the remote sensing monitoring of accumulated snow, meadow, traffic settlement;

Said data aggregation to accumulated snow comprises: snow depth, accumulated snow coverage rate and low temperature continuous days;

Said data aggregation to the meadow comprises: meadow output, meadow availability, herbage height, herbage deposit, livestock shed facility and herdsman's economic situation;

Said data aggregation to the traffic settlement comprises: pastoral area traffic communication situation and settlement distribute.

8. the method for early warning of pastoral area as claimed in claim 6 snow disaster is characterized in that: livestock supporting body data and Data acquisition, are through being that the releve of elementary cell carries out meteorology, herdsman livestock, socioeconomic ground monitoring with the county with herding the family;

Said data aggregation to meteorology comprises: precipitation, temperature, wind-force and low temperature continuous days;

Said data aggregation to the herdsman livestock comprises: herdsman and livestock body condition, structure and quantity;

Said socioeconomic data aggregation is comprised: forage reserves, livestock shed, house, medical treatment and herdsman's income.

9. like the method for early warning of the arbitrary described pastoral area of claim 1 to 5 snow disaster, it is characterized in that: preparatory information, risk management and the early warning decision prediction scheme of the integrated early warning system of described multi-source information issue comprises that snow disaster endangers zoning map pastoral area snow disaster advanced warning grade figure, pastoral area strength of combatting natural disaster evaluation map and provides and combat a natural disaster the prediction scheme of taking precautions against natural calamities.

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