CN111291488A - Aerial seeding afforestation method based on meteorological parameters - Google Patents
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Abstract
The invention discloses an aerial seeding afforestation method based on meteorological parameters, which comprises the following steps: (1) before the aerial sowing, determining the optimal time range of the aerial sowing according to historical meteorological parameters; (2) performing air seeding operation according to the determined optimal time range before air seeding; (3) in the air seeding process, determining whether the air seeding operation is suitable or not according to the real-time meteorological parameters; (4) after the aerial sowing is finished, the meteorological parameters in the month and N days after the aerial sowing are used as independent variables, the vegetation coverage is used as dependent variables, and a regression fitting equation is constructed; (5) and (4) comparing the influence of different dependent variables on independent variables through multiple regression analysis according to the regression fitting equation in the step (4) to obtain meteorological parameters with the maximum influence. The method can improve the efficiency of the aerial seeding afforestation, reduce the operation cost, provide a basis for developing research on main meteorological factors influencing the aerial seeding effect and provide industry-integrated meteorological guarantee service for improving the aerial seeding afforestation effect.
Description
Technical Field
The invention relates to an aerial seeding afforestation method based on meteorological parameters.
Background
The air seeding afforestation has been developed for 60 years, has the advantages of high speed, labor saving, low cost, wide range of motion and easy scale benefit formation, and becomes an effective measure for improving the vegetation coverage rate of forests and preventing and controlling sand in desert regions. The airplane is started to operate during the air seeding afforestation, and the requirement on meteorological conditions is very strict. Whether the seeds can emerge and the seedlings are directly influenced by the factors such as precipitation amount, strength and the like after the air seeding, particularly in desert regions with precipitation amount of less than 200 mm, the air stripping, sand pressure, drought and runoff scouring have great influence on the emergence and the seedling protection due to less drought and rain, large wind and much sand, and if the wind speed is too high, the seeds can be displaced and the seedlings are buried by wind erosion and sand to influence the air seeding effect. Therefore, the selection of the sowing time, the flying sowing taking-off and landing operation and the weather conditions of the seedling emergence period after sowing are directly related to the success or failure of the flying sowing afforestation. At present, an air seeding afforestation service flow and a content system based on meteorological parameters are lacked.
Disclosure of Invention
The purpose of the invention is as follows: the invention aims to provide a comprehensive and systematic aerial seeding afforestation method based on meteorological parameters.
The technical scheme is as follows: the invention discloses an aerial seeding afforestation method based on meteorological parameters, which is characterized by comprising the following steps:
(1) before the aerial sowing, determining the optimal time range of the aerial sowing according to historical meteorological parameters;
(2) performing air seeding operation according to the determined optimal time range before air seeding;
(3) in the air seeding process, determining whether the air seeding operation is suitable or not according to the real-time meteorological parameters;
(4) after the aerial sowing is finished, the meteorological parameters in the month and N days after the aerial sowing are used as independent variables, the vegetation coverage is used as dependent variables, and a regression fitting equation is constructed;
(5) and (4) comparing the influence of different dependent variables on independent variables through multiple regression analysis according to the regression fitting equation in the step (4) to obtain meteorological parameters with the largest influence, and guiding the next aerial seeding operation.
Has the advantages that: compared with the prior art, the invention has the following remarkable advantages:
(1) the invention provides an air seeding afforestation method based on analysis, forecast and tracking monitoring before air seeding, during air seeding, after air seeding, from the perspective of improving the success rate of air seeding afforestation in desert regions, the optimal air seeding time in the region is determined, the optimal weather condition during air seeding is ensured, the dynamic change of meteorological factors during the period from air seeding to seedling emergence is tracked, and the contribution of meteorological composition factors in each stage to the air seeding afforestation effect is determined. The method provides a targeted meteorological analysis material at the early stage of the air seeding, provides an aging forecast service at the implementation stage of the air seeding and provides meteorological monitoring information at the later stage of the air seeding.
(2) The method can improve the efficiency of the aerial seeding afforestation, reduce the operation cost, provide a basis for developing the main meteorological factor which influences the aerial seeding effect, provide meteorological data support for developing the aerial seeding afforestation work of a forestry bureau, provide a theoretical basis for the correlation study of the emergence rate of different shrubs and the meteorological factor in the aerial seeding afforestation in the desert area in future, provide an idea for developing the ecological meteorological service work of the aerial seeding afforestation in the desert area in the next step, and provide a reference for the aerial seeding afforestation meteorological guarantee service flow in different areas.
Drawings
FIG. 1 is a schematic flow diagram of the present invention;
FIG. 2 is the distribution rule of the average rainfall value in Bayanhaote 1988 and 2017;
FIG. 3 is the average rainfall of Bayangtao 1988 and 6 months each year 2017;
FIG. 4 is the monthly average air temperature distribution rule of Bayangtao 1988 and 2017;
FIG. 5 is the average daily distribution law of strong wind and sandstorm in Bayanhaote 1988 and 2017;
Detailed Description
The technical scheme of the invention is further explained by combining the attached drawings.
As shown in FIG. 1, the aerial seeding afforestation method based on meteorological parameters comprises the following steps:
(1) before the aerial seeding, determining the optimal time range of the aerial seeding according to historical meteorological parameters, wherein the historical meteorological parameters comprise the average rainfall, the evaporation capacity, the average temperature, the day and night temperature difference, the number of strong wind days, the number of sand and dust days, the average sunshine time and the record of dominant afforestation vegetation varieties in the region of nearly 30 years. Wherein the monthly average rainfall P, the monthly average temperature T, the wind and day number W and the dust and day number S are main judgment factors of the optimal air speed, and the rest are secondary judgment factors; the determination of the optimal air-borne broadcast time needs to meet the following conditions: p is more than or equal to 20mm and less than or equal to 50mm, T is more than or equal to 20 ℃ and less than or equal to 30 ℃, W is less than or equal to 3 days/month, and S is less than or equal to 1 day/month.
For example, Bayangtao, one of the areas where the aeroseeding is carried out in Alahin, selects the fast-growing and drought-resistant flower stick of the rural shrub tree species, Calligonum rubicundunm and Artemisia selengensis as the aeroseeding species according to the record of the Alahin forestry department about the species of the dominant afforestation vegetation. The basic conditions required for vegetation growth are moisture, temperature and light. The average sunshine hours of the local calendar year is 3061.1h, the illumination is sufficient, according to historical meteorological parameters, the strong wind and the sand dust are common weather phenomena in the local, the strong wind can effectively help the sand to cover the seeds, but the seeds are easily uncovered by the strong wind and the sand dust due to too many days, and the aerial work of the aerial seeding is not facilitated.
Fig. 2 shows the average rainfall value distribution rule of 30 years in 1988 + 2017 by the local weather bureau, as shown in fig. 2, from 6 months, the rainfall tends to increase, and reaches the maximum in 7 months, but the single rainfall in 7 months is about 50mm, i.e. the rainstorm or heavy rain level, so that surface soil loss and larger runoff are easily caused in desert regions with sparse vegetation, so that the seeds are not covered with sand after sowing and bud flashing, and according to the average rainfall in each 6 th day of each 6 months in 30 years (fig. 3), the last day is greater than the middle day, and relatively sufficient rainfall after sowing is favorable for germination and emergence. According to the change value of the average air temperature in 30 months (figure 4), the air temperatures in 6 months, 7 months and 8 months all reach more than 20 ℃, and the temperature is highest in the whole year. The average daily number of strong wind and sand storm in each month of 30 years in the local area (fig. 5) shows that the daily number of strong wind and sand storm in 5 months reaches the maximum and gradually decreases from 6 months. And (4) determining the most suitable seeding time period of the area to be 6 middle of the month by integrating the three meteorological elements.
(2) Performing air seeding operation according to the determined optimal time range before air seeding;
(3) and in the air broadcasting process, determining whether the air broadcasting operation is suitable or not according to the real-time meteorological parameters. The real-time meteorological parameters are rainfall, wind speed and wind direction of a flying broadcast site, the real-time meteorological parameters are measured by an automatic meteorological station and a handheld wind direction and anemoscope, real-time acquisition is carried out every n hours, and n is 1,2,3 … … 12, preferably n is 3. The values of the parameters and whether the broadcast is suitable are shown in the following table.
TABLE 1 suitable range of rainfall for air-seeding operation
Note: "√" represents an aerial work suitable for aerial seeding, and "x" represents an aerial work unsuitable for aerial seeding.
TABLE 2 proper range of wind speed in flying seeding operation
The standard of the wind speed influence is different according to different types of aerial seeding tasks, and the types of the aerial seeding tasks executed locally are all transport-5 type transporters. The weather forecast can help the operation plane to avoid strong convection weather, correct crosswind in time and improve the seed falling accuracy, thereby obtaining the suitable degree of rainfall and the suitable range of wind speed in the air-seeding operation.
(4) And after the aerial sowing is finished, the meteorological parameters in the month and N days after the aerial sowing are used as independent variables, the vegetation coverage is used as dependent variables, and a regression fitting equation is constructed. The meteorological parameters comprise the rainfall in the current month, the average air temperature in the current month, the average rainfall N days after the air seeding, the average air temperature N days after the air seeding and the like.
For example, taking data of 2013 and 2017 in a certain area as an example, the monitored rainfall x in the current month of the aerial seeding1Average temperature in the month x2And average rainfall x of 3 months after aerial sowing3And a monthly mean air temperature x of 3 months4As independent variable, the variation value of the annual aerial seeding afforestation vegetation coverage rate investigated by forestry departments is used as dependent variable y, multiple regression analysis is carried out to obtain the complex correlation coefficient R of 0.9849, which shows that the meteorological factor has better correlation with the aerial seeding effect, the F value can obtain the regression effect, the P value can obtain the x value, the F value and the dependent variable have obvious regression effect1And x3Has a correlation with y, and yields a regression equation D: y 10.151+0.075x1-0.930x2+0.028x3+0.381x4Namely, the rainfall of the current month of the aerial sowing and the average rainfall of the 3 months after the aerial sowing are all in positive correlation with the vegetation coverage rate of the aerial sowing.
(5) And (4) comparing the influence of different dependent variables on independent variables through multiple regression analysis according to the regression fitting equation in the step (4) to obtain meteorological parameters with the largest influence, and guiding the next aerial seeding operation.
The obtained complex correlation coefficient R is 0.9849 (table 3), which shows that the meteorological factor has better correlation with the air-borne broadcast effect, the Significance F value in the variance analysis table (table 4) can be used for obtaining the regression effect of the independent variable and the dependent variable, the P-value list in the regression parameter table (table 5) can be used for obtaining the numerical value x1 and x3 and y have correlation, wherein the precipitation in the current month is the main influence factor, and the influence of the air temperature on the air-borne broadcast effect is not obvious.
TABLE 3 regression analysis Table
| Multiple R | 0.984931 |
| R Square | 0.970089 |
| Adjusted R Square | 0.958124 |
| Standard error of | 0.391083 |
TABLE 4 ANOVA TABLE
| df | SS | MS | F | Significance | |
| Regression analysis | |||||
| 4 | 49.60354 | 12.40089 | 81.08024 | 1.40078E-07 | |
| |
10 | 1.529458 | 0.152946 | ||
| Total of | 14 | 51.133 |
TABLE 5 regression parameter Table
| Coefficients | Standard error of | t Stat | P-value | Lower 95％ | Upper 95％ | |
| Intercept | 10.15054 | 5.557407 | 1.826489 | 0.097735 | -2.23213253 | 22.53322 |
| |
0.075143 | 0.00567 | 13.25285 | 1.14E-07 | 0.062509981 | 0.087777 |
| X Variable 2 | -0.92952 | 0.496028 | -1.87392 | 0.090424 | -2.03473456 | 0.175703 |
| |
0.02826 | 0.010252 | 2.756448 | 0.020253 | 0.005416341 | 0.051103 |
| |
0.381314 | 0.323463 | 1.178849 | 0.265746 | -0.339406 | 1.102033 |
Claims (9)
1. An aerial seeding afforestation method based on meteorological parameters is characterized by comprising the following steps:
(1) before the aerial sowing, determining the optimal time range of the aerial sowing according to historical meteorological parameters;
(2) performing air seeding operation according to the determined optimal time range before air seeding;
(3) in the air seeding process, determining whether the air seeding operation is suitable or not according to the real-time meteorological parameters;
(4) after the aerial sowing is finished, the meteorological parameters in the month and N days after the aerial sowing are used as independent variables, the vegetation coverage is used as dependent variables, and a regression fitting equation is constructed;
(5) and (4) comparing the influence of different dependent variables on independent variables through multiple regression analysis according to the regression fitting equation in the step (4) to obtain meteorological parameters with the largest influence, and guiding the next aerial seeding operation.
2. The aerial seeding forestation method based on meteorological parameters according to claim 1, wherein the historical meteorological parameters in the step (1) comprise monthly average rainfall, evaporation capacity, monthly average air temperature in each season, day-night temperature difference, heavy wind days, sand days, average sunshine time and dominant forestation vegetation variety records in the region.
3. The aerial seeding forestation method based on meteorological parameters, which is characterized in that in the step (1), the average rainfall per month P, the average air temperature per month T, the number of days of strong wind W and the number of days of sand dust S are main judgment factors of the optimal aerial seeding time, and the rest are secondary judgment factors; the determination of the optimal air-borne broadcast time needs to meet the following conditions: p is more than or equal to 20mm and less than or equal to 50mm, T is more than or equal to 20 ℃ and less than or equal to 30 ℃, W is less than or equal to 3 days/month, and S is less than or equal to 1 day/month.
4. The aerial seeding forestation method based on meteorological parameters, which is characterized in that the real-time meteorological parameters in the step (3) are rainfall, wind speed and wind direction of an aerial seeding site, and the real-time acquisition is carried out every n hours, wherein n is 1,2,3 … … 12.
5. The aerial seeding forestation method based on meteorological parameters, wherein the condition suitable for aerial seeding is that the rainfall is less than 24.9 mm.
6. The aerial seeding forestation method based on the meteorological parameters, wherein when the wind direction is positive crosswind, the wind speed is less than or equal to 4 grades, which is a condition suitable for aerial seeding; the wind direction is downwind, the wind speed is less than or equal to 5 grades, and the condition suitable for aerial seeding is met; the wind direction is the reverse side wind, the wind speed is less than or equal to 7 grades, and the condition suitable for air seeding is met.
7. The aerial seeding forestation method based on meteorological parameters according to claim 4, wherein the real-time meteorological parameters are measured by using an automatic meteorological station and a handheld anemometer.
8. The method for on-air afforestation based on meteorological parameters according to claim 1, wherein the meteorological parameters in the step (4) comprise current-month rainfall, current-month average air temperature, average rainfall N days after on-air and average air temperature N days after on-air.
9. The aeroseeding forestation method based on meteorological parameters according to claim 1, wherein N is more than or equal to 10 in step (4).
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| CN112947574A (en) * | 2021-03-17 | 2021-06-11 | 中国矿业大学(北京) | Unmanned aerial vehicle aerial sowing operation design method |
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| CN106218890A (en) * | 2016-08-31 | 2016-12-14 | 宁夏大学 | A kind of accurate plant seeds by airplane system based on unmanned plane |
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| CN106218890A (en) * | 2016-08-31 | 2016-12-14 | 宁夏大学 | A kind of accurate plant seeds by airplane system based on unmanned plane |
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| 傅锡儒: "飞机播种造林与气象因子的关系" * |
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| CN112947574A (en) * | 2021-03-17 | 2021-06-11 | 中国矿业大学(北京) | Unmanned aerial vehicle aerial sowing operation design method |
| CN112947574B (en) * | 2021-03-17 | 2022-05-31 | 中国矿业大学(北京) | Unmanned aerial vehicle aerial sowing operation design method |
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