CN106815658A - A kind of agricultural arid early warning system - Google Patents
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Abstract
The invention discloses a kind of agricultural arid early warning system, the agricultural arid early warning system includes：Unidirectional agricultural arid index is calculated；Integrated agriculture drought index is calculated, and whether certain point area occurs arid in judging region with reference to unidirectional agricultural arid index；Zoning property agricultural drought indices and time agricultural drought indices, determine scope, time that agricultural arid occurs, and arid state of development is judged, send corresponding drought early warning.The system incorporates all more ripe drought index in theory and practice and is monitored early warning to regional agriculture arid, the multinomial factor for causing agricultural arid is considered, improve agricultural arid monitoring reasonability, the spatial and temporal scales of agricultural arid monitoring are expanded, more flexibly to the agricultural arid of different zones and different periods, a situation arises and degree is analyzed to allow user, improves the applicability of system.
Description
Technical field
The present invention relates to agricultural arid electric powder prediction, a kind of agricultural arid early warning system is specifically related to.
Background technology
In recent years, the frequency and intensity of the extreme weather events such as the arid for being caused by Global climate change are in significant increasing
Plus trend, the sustainable development to the ecosystem and human society causes far-reaching influence.Data shows that 21 century is global dry
The risk of drought will be further increased, how the time that accurate Monitoring of Drought occurs, the degree that assessment arid occurs slows down arid
The influence for causing has turned into important scientific issues urgently to be resolved hurrily.
Meanwhile, arid is difficult to directly observe its time of origin, evolution and coverage as a kind of complicated phenomenon,
Drought event is described by drought index mainly at present thus.Existing agricultural arid monitoring technology generally chooses one
Or multiple drought indexs, meteorology, the agricultural data of region certain period are obtained, quantitative-qualitative analysis are carried out to result of calculation,
Judge whether agricultural arid occurs in the period, time, the degree and not of arid generation have been illustrated if it there is agricultural arid
The duration aspect for coming, while providing corresponding solution.Different from meteorological drought, different crops, tillage method and
It is different that soil is constituted to the demand of moisture, thus the qualitative judgement that occurs to agricultural arid and qualitative assessment all should be because
Ground suiting measures to different conditions, the characteristics of either the calculating of drought index or the evaluation of index should all embody region.
For prior art, only a certain key element is carried out for agricultural arid to the calculating of drought index, although in spy
Determine region and achieve preferable effect but whether the index extension that can carry out spatial and temporal scales need to be proved, and these
Index fails reflection to the resistance and hysteresis effect of arid for crops, and anticipation trend is also with the different of selecting index
Different, these problems cause different zones index result without comparativity, and predict the outcome and there is certain deviation.
The content of the invention
For the above-mentioned problems in the prior art, there is provided a kind of agricultural arid early warning system, from the hair of agricultural arid
Life reason is started with, and specifies water requirement of the different crops in its each growth, with reference to meteorological, soil data, choose it is multiple compared with
For science, objective, strong operability drought index are monitored to agricultural arid.
To achieve the above object, the effect above is reached, the present invention is to be achieved through the following technical solutions：
A kind of agricultural arid early warning system, including following steps：
Step one：Unidirectional agricultural arid index is calculated；
1st, Standardized Precipitation index (SPI)
2nd, relative moisture of the soil (Rsm)
3rd, Crop water deficits index (CWDI)
4th, it is continuous without effective precipitation (snowfall, accumulated snow) number of days (Dnp)
5th, precipitation anomaly percentage
Step 2：Integrated agriculture drought index is calculated：Certain point is regional in judging region with reference to unidirectional agricultural arid index
Whether arid there is；
Step 3：Zoning property agricultural drought indices and time agricultural drought indices：Determine the model that agricultural arid occurs
Enclose, the time, and to arid state of development judge, send corresponding drought early warning；
The calculating of three steps, just can determine whether agricultural arid situation of the current region in a certain period more than, dry to agricultural
Drought is estimated.
Preferably, the Standardized Precipitation index (SPI) of the step one is calculated as：Assuming that the precipitation of a certain period is x,
Its meet Gamma distribution probability density function be：
In formula：α ＞ 0 are form parameter；β ＞ 0 are scale parameter；X ＞ 0 are precipitation, and unit is mm；Γ (α) is Gamma
The cumulative probability density function of distribution, be：
Value on α and β can be adopted and calculate estimate with the following method：
In above formula:xiIt is the sample value of precipitation,It is the average value of precipitation, n is the length of the sequence of calculation.By
This can calculate the cumulative probability of random time length according to above-mentioned equation g (x)：
Due to the situation not comprising x=0 in Gamma equations, if occurring precipitation in time scale in practice for 0 feelings
Condition, then calculate cumulative probability density using following equations:
H (x)=q+ (1-q) G (x)
In above formula：Q is the probability that precipitation is 0, that is, precipitation is 0 quantity in setting m as precipitation, then have q=m/
n；
Normal state treatment is carried out to above-mentioned equation, will the above-mentioned counted standardized normal state point of probable value substitution of equation institute
Cloth function：
Above formula can be solved using following approximate formula in actual applications：
When 0 ＜ H (x)≤0.5：
As 0.5 ＜ H (x) ＜ 1：
In above formula：C0=2.515517, c1=0.802853, c2=0.010328, d1=1.432788, d2=
0.189269, d3=0.001308.
Preferably, the relative moisture of the soil (Rsm) of the step one is calculated as：Relative moisture of the soil is calculated as follows formula：
In formula：Rsm is the average relative moisture of the soil of figure layer；A is Crop development phase adjustment factor, and seedling stage is 0.9 crop water
Point critical period is 1.1, and remaining puberty is 1, pair with parameter a, Relational database can be set up according to region chief crop, really
It is scheduled on the value in different times a for Different Crop；wiIt is i-th layer of water content of soil (%)；fciIt is i-th layer of field of soil
Between water-holding capacity (%)；N is the soil layer number of observation, should be each layer of addition power by thickness when each soil horizon thickness is different
Weight.
Preferably, the Crop water deficits index (CWDI) of the step one is calculated as：The crop water of certain time loses
The calculation of adactylism number is as follows：
In formula：ETmIt is certain section of Penman-Monteith formula of time (mm), because agricultural arid is lasting water deficit so as to influence
One kind arid caused by plant normal growth, therefore the parameter and remaining parameter take the cumulant of 10 days, calculate 10 days
Water deficit index accumulated value；PiWith IiThe respectively precipitation and irrigation volume of monitored area section time, as it was previously stated, taking 10
It cumulant, if detection zone lacks the monitoring to irrigation volume, can be filled by the corresponding conventional crop control measures estimation in region
Irrigate date and irrigation volume；
Because Crops Drought is mainly reflected in cumulative effect, moisture of the water deficit index typically to continuous 5 periods loses
Adactylism number weighted sum：
CWDI=a × CWDIi+b×CWDIi-1+c×CWDIi-2+d×CWDIi-3+e×CWDIi-4
In formula：CWDI is certain section of accumulation Crop water deficits index of time；CWDIi、CWDIi-1、CWDIi-2CWDIi-3、
CWDIi-4The water deficit index of this time and preceding 4 time respectively；A, b, c, d, e are respectively 5 weights of period of the above
Value, typically value is respectively：0.3、0.25、0.2、0.15、0.1；
ET in above formulamCan be calculated using following formula：
ETm=Kc·ET0
In formula：ET0It is the crop reference evapotranspiration of 10 days；KcIt is the crop coefficient of certain crop, it is more complete for data
Monitored area, sets up crop coefficient database, and unconditional region can set up FAO and recommend crop coefficient database or directly fortune
The numerical value that is determined by experiment with neighborhood sets up database；
ET0It is calculated using following formula：
The formula parameter is more, and now the meaning and calculation to each parameter are explained in detail that (what be should be noted is a bit
Required by the formula is daily evapotranspiration rate of referential crops, finally result is sued for peace so as to obtain the accumulated value of 10 days)：
T：Daily mean temperature (DEG C), is obtained, i.e., by the mean value calculation of daily maximum temperature and daily minimal tcmperature：
es：Same day saturation vapour pressure (kPa).The saturation vapour pressure of one day is related to daily temperature is worked as, therefore can use gas
Temperature calculates same day saturation vapour pressure, and calculation is as follows：
The reckoning equation of saturation vapour pressure is nonlinear equation as can be seen from the above equation, therefore uses daily mean temperature direct
Lower result can be caused if solution, therefore the saturation vapour for being calculated using daily maximum temperature and the lowest temperature in the present invention
The average value of pressure：
ea：Same day actual water vapor pressure (kPa), for that can be calculated with following formula with determining the area of relative humidity：
ea=Rh·es
In formula：RhIt is same day average relative humidity (%)；esIt is same day saturation vapour pressure；
Same day actual water vapor pressure can also be tried to achieve using dew-point temperature instead of temperature：
In formula：TdewIt is dew-point temperature (DEG C), that is to say, that actual water vapor pressure is the saturation vapour pressure under dew-point temperature；
Δ：The saturation vapour pressure slope of curve, i.e. saturation vapour pressure with temperature Change speed, that is, above-mentioned reckoning saturation
The derivative value of vapour pressure equation：
In formula：T is temperature (DEG C)；
Rn：Day net radiation amount (MJm-2·d-1).Net radiation amount be obtain solar radiation with reflection solar radiation it
Difference：
Rn=Rns-Rnl
In formula：RnsIt is the net short-wave radiation for obtaining；RnlIt is the long wave net radiation of expenditure.Net short-wave radiation RnsBy receive and
The balance of solar radiation relation of reflection is calculated：
Rns=(1- α) Rs
In formula：RsIt is day solar radiation (MJm-2·d-1)；α is surface albedo, can be with profit for conditional region
More accurate surface albedo is obtained with satellite remote sensing date inverting, conditional can not take green meadow reference crop
Albedo：0.23, and modified according to provincial characteristics；
Long-wave radiation Rnl4 power to earth's surface absolute temperature are related, and by Stefan-Boltzmann constant quantificational expression.
Long wave is also influenceed by factors such as steam, clouds simultaneously in practice, it is therefore desirable to take into account these factors.Given below
Formula allows for humidity and influence of the cloud amount to long-wave radiation, with the addition of two computing formula for correcting the factor：
In formula：TMax, KWith TMin, KRespectively same day highest absolute temperature and minimum absolute temperature, according to K=DEG C+273.16
Relation changed；σ is Stefan-Boltzmann constant, and its value is 4.903 × 10-9MJ K-4m-2day-1；eaIt is actual water
Vapour pressure；RsIt is solar radiation；RsoIt is clear sky solar radiation (MJm-2·d-1)；
Determine clear sky solar radiation RsoThen will definitely outer solar radiation Ra.Extraterrestrial radiation has with geographic latitude and day sequence
Close, can be determined by following formula：
In formula：IscBe solar constant, i.e. 4.921MJ/ (m2·h)；E0It is Eccentricity of the earth correction factor；ω is ground
The angular speed of revolutions, i.e. 0.2618rad/h；TSRIt is sunrise time；δ is the solar declination of Circular measure；φ is the ground of Circular measure
Reason latitude；
Eccentricity of the earth E0Can be calculated with following formula：
In formula：dnIt is day sequence number, takes the serial number 1 in the January 1 of each year, the serial number 365 on December 31 is (to calculate
Convenient acquiescence only 28 days all 2 months, in practice because the presence in leap year can cause certain trueness error, also can be before calculating
Judge whether the time is the leap year so that it is determined that day sequence)；
Solar declination δ can be estimated using below equation：
In formula：dnIt is day sequence number, the implication with equation is identical, the solar declination obtained by calculating is Circular measure；Sunrise time
TSRCan be calculated with following formula：
In formula：δ is the solar declination (rad) of Circular measure；φ is the geographic latitude (rad) of Circular measure；ω is earth rotation
Angular speed；
The energy for wanting accurate predicting radiation energy to be lost through air is more difficult, it is assumed here that extraterrestrial radiation is passed through
The loss amount that air reaches ground is 20%, can change the value according to the difference of the estimation result in region and measured result afterwards.
Based on this it is assumed that the possible maximum solar in earth surface certain point：
Rso=0.8 × Ra
In formula：RaIt is solar radiation outside ground；
G：Soil heat flux.Soil heat flux is one relative to net radiation RnFor very little value, especially in earth's surface
During by vegetative coverage, therefore this can omit under less time scale.For moon yardstick soil heat flux, it can be assumed that
It is constant 2.1MJm in appropriate depth of soil, soil heat capacity-3℃-1, then following estimation equation can have been obtained：
G=0.14 (Tmonthi-Tmonthi-1)
In formula：TmonthiIt is the temperature on average of i-th month；Tmonthi-1It is upper monthly mean temperature.u2：Wind at two meters from the ground
Fast (m/s), other are highly observed the wind speed for obtaining and can be corrected using following formula：
In formula：uzIt is the wind speed (m/s) surveyed at z-height；Z is placement height (m) of airspeedometer.γ：Psychrometer is normal
(kPa DEG C of number-1), can be calculated by following formula：
γ=0.665 × 10-3P
In formula：P is atmospheric pressure (kPa)；Z is local height above sea level (m).
Preferably, the continuous of the step one is calculated as without effective precipitation (snowfall, accumulated snow) number of days (Dnp)：For not having
Carry out the region of soil moisture content monitoring, it is possible to use continuous this index without effective precipitation replaces relative moisture of the soil Rsm, is applicable
In rain-fed agriculture region：
In formula：DnpiPrecipitation Day for intra day ward less than effectiv precipitation；A is season adjustment factor, (March to 5 in spring
Month) it is 1, summer (June to August) is 1.4, and autumn and winter (September to November and December were to 2 months) they are 0.8；
Also season can be divided using mean temperature, i.e., is the summer when waiting 22 DEG C of mean temperature ＞ being within 5 days one to wait
In season, wait 10 DEG C of mean temperature ＜ to be is winter, and it between 10 DEG C~20 DEG C is spring and autumn to wait mean temperature, and 22 are raised to by 10 DEG C
DEG C it is spring, 10 DEG C is dropped to for autumn by 22 DEG C；
Can judge whether the rainfall of a day is effective using following formula：
In formula：P is intra day ward (mm)；P0It it is day effectiv precipitation critical value (mm), generally, in the water of crop
Divide critical period effective precipitation to take 5mm/day, 3mm/day is taken in remaining stage effective precipitation of plant growth；
Be should be noted during using the index：1st, the index is applied to the dry crop of rain-fed agriculture region；2nd, such as it is in crop
Growth needs water critical zone, continuous should accordingly be expanded without effective precipitation number of days to what is be calculated.
Preferably, the precipitation anomaly percentage of the step one is calculated as：Certain period precipitation anomaly percentage (Pa)
It is calculated as follows：
In formula：P is the precipitation (mm) of certain period；It is the same period average precipitation (mm) of calculation interval；δ is adjusted for season
Section coefficient (division about season has been discussed above), summer is 1.6, and spring is 1, and winter is 0.8；
Preferably, the step 2 integrated agriculture drought index is calculated as：
These parameters are chosen according to monitored area feature and to the Grasping level of the area observation data to be calculated and done
Drought classification, summation is weighted by the arid grade of gained：
In formula：XiIt is i-th drought index for being calculated；piIt is the weight of i-th drought index for being calculated, andAssign all drought indexs equal weight when monitoring and starting, according to the comparison of result and field data
The weighted value of each index is adjusted, the need for it is finally met the regional agriculture draught monitor；
The time (being accurate to every 10 days) and do that can determine that certain point arid in region occurs are calculated by this step
The degree that drought occurs.
Preferably, the step 3 is specifically calculated as：
For a certain region, its overall degree of drought can have following formula to determine：
In formula：RiIt is the agricultural arid index of certain arid period；A is the total sown area in this area；AiFor occur light drought, in
Non-irrigated, weight drought, the farming region area of special drought；aiIt is light non-irrigated, middle non-irrigated, weight drought, the weight of special drought grade, a is taken here1=5%, a2=
15%, a3=30%, a4=50%；
For longer time yardstick, its arid degree can have greatly changed, it is necessary to an index carrys out comprehensive saying
A situation arises and degree for arid in bright this section of period.Time agricultural arid index is comprehensively commented for a certain period agricultural arid intensity
Estimate index.The index can be estimated to more than two drought process, and calculation is as follows：
In formula：Ti is time agricultural arid index；Hop count when T is total；TijFor this when it is disconnected in there is the number of days of arid；aiFor
The weight of each grade arid, respectively 5%, 15%, 30%, 40%.
The calculating of three steps, just can determine whether agricultural arid situation of the current region in a certain period more than, dry to agricultural
Drought is estimated.According to national standard, the agricultural arid situation in certain region can be carried out following qualitative description：
1st, agricultural arid is lasting, i.e. the period has occurred agricultural arid, and arid grade a period is equal earlier above.
2nd, there is agricultural arid in agricultural arid development, the i.e. period, and arid grade increased more for the previous period.
3rd, agricultural arid relaxes, i.e. the period has occurred agricultural arid, and arid grade has been reduced more for the previous period.
4th, agricultural arid is released, i.e. the period does not occur agricultural arid, and for the previous period there is arid.
According to regional agriculture arid, a situation arises, and corresponding drought early warning is sent with reference to arid grade, is local agricultural
Production provides arid defensive measure, to reduce the loss that arid is caused.
When setting up the system for a certain region, the basic data in the region should be first collected, and be updated at any time
To ensure to the ageing of the area monitoring.Can be divided into geographical number for the data information that a region carries out agricultural arid monitoring
According to, meteorological data and agricultural data：
1st, geodata：Including monitored area scope, longitude and latitude, height above sea level etc..The warp of the other region weather monitoring website
Latitude is also necessary with height above sea level.
2nd, meteorological data：Etc. the precipitation observed day by day including the region, temperature, wind speed, relative humidity, solar radiation, remove
Recent meteorological data, in addition it is also necessary to the region history meteorological data of at least 30 years, so that the average value for obtaining can be represented
The climatic characteristic in the region.
3rd, agricultural data：The present status of land utilization in the region, land management unit, main long-term cropping, cultivated area, often
Rule Agricultural management system etc..
The foundation of the system needs to be integrated the data of above-mentioned three types so as to the data that cannot directly observe
Calculated, comprehensive meteorological, soil and agricultural data, whether agricultural arid and agricultural arid are occurred in a certain period to region
Degree is monitored, and so as to carry out timely early warning to agricultural arid, guiding agricultural production takes necessary defensive measure,
Reduce the agricultural losses that arid is caused.
Brief description of the drawings
Fig. 1 is agricultural arid early warning system flow chart of the present invention.
Specific embodiment
In order to make the purpose , technical scheme and advantage of the present invention be clearer, with reference to embodiments, to the present invention
It is further elaborated.It should be appreciated that the specific embodiments described herein are merely illustrative of the present invention, it is not used to
Limit the present invention.
Application principle of the invention is explained in detail below in conjunction with the accompanying drawings.
As shown in figure 1, a kind of agricultural arid early warning system of the embodiment of the present invention, including following steps：
S101：Unidirectional agricultural arid index is calculated；
(1) Standardized Precipitation index (SPI)
(2) relative moisture of the soil (Rsm)
(3) Crop water deficits index (CWDI)
(4) it is continuous without effective precipitation (snowfall, accumulated snow) number of days (Dnp)
(5) precipitation anomaly percentage
S102：Integrated agriculture drought index is calculated：Certain point area is in judging region with reference to unidirectional agricultural arid index
It is no that arid occurs；
S103：Zoning property agricultural drought indices and time agricultural drought indices：Determine agricultural arid occur scope,
Time, and arid state of development is judged, send corresponding drought early warning；
The calculating of three steps, just can determine whether agricultural arid situation of the current region in a certain period more than, dry to agricultural
Drought is estimated.
Wherein, the Standardized Precipitation index (SPI) of S101 is calculated as：Assuming that the precipitation of a certain period is x, its satisfaction
Gamma distribution probability density function be：
In formula：α ＞ 0 are form parameter；β ＞ 0 are scale parameter；X ＞ 0 are precipitation, and unit is mm；Γ (α) is Gamma
The cumulative probability density function of distribution, be：
Value on α and β can be adopted and calculate estimate with the following method：
In above formula:xiIt is the sample value of precipitation,It is the average value of precipitation, n is the length of the sequence of calculation.By
This can calculate the cumulative probability of random time length according to above-mentioned equation g (x)：
Due to the situation not comprising x=0 in Gamma equations, if occurring precipitation in time scale in practice for 0 feelings
Condition, then calculate cumulative probability density using following equations:
H (x)=q+ (1-q) G (x)
In above formula：Q is the probability that precipitation is 0, that is, precipitation is 0 quantity in setting m as precipitation, then have q=m/
n；
Normal state treatment is carried out to above-mentioned equation, will the above-mentioned counted standardized normal state point of probable value substitution of equation institute
Cloth function：
Above formula can be solved using following approximate formula in actual applications：
When 0 ＜ H (x)≤0.5：
As 0.5 ＜ H (x) ＜ 1：
In above formula：C0=2.515517, c1=0.802853, c2=0.010328, d1=1.432788, d2=
0.189269, d3=0.001308；
With 2,3 SPI values of month yardstick, according to relevant criterion monitoring agricultural arid, a situation arises in the present invention；
The SPI indexes of calculating can according to the form below the period damage caused by a drought is evaluated：
Wherein, the relative moisture of the soil (Rsm) of S101 is calculated as：Relative moisture of the soil drought index can reflect crop profit
The situation reduced with moisture, be one of the index for characterizing soil drought, and relative moisture of the soil is calculated as follows formula：
In formula：Rsm is the average relative moisture of the soil of figure layer；A is Crop development phase adjustment factor, and seedling stage is 0.9 crop water
Point critical period is 1.1, and remaining puberty is 1, pair with parameter a, Relational database can be set up according to region chief crop, really
It is scheduled on the value in different times a for Different Crop；wiIt is i-th layer of water content of soil (%)；fciIt is i-th layer of field of soil
Between water-holding capacity (%)；N is the soil layer number of observation, should be each layer of addition power by thickness when each soil horizon thickness is different
Weight.
Preferably, the Crop water deficits index (CWDI) of the S101 is calculated as：Crop water deficits index is to characterize
One of index of Crop water deficits degree, will form agriculture dry when crop water is not being met within certain duration
Drought.The calculation of certain section of Crop water deficits index of time is as follows：
In formula：ETmIt is certain section of Penman-Monteith formula of time (mm), because agricultural arid is lasting water deficit so as to influence
One kind arid caused by plant normal growth, therefore the parameter and remaining parameter take the cumulant of 10 days, calculate 10 days
Water deficit index accumulated value；PiWith IiThe respectively precipitation and irrigation volume of monitored area section time, as it was previously stated, taking 10
It cumulant, if detection zone lacks the monitoring to irrigation volume, can be filled by the corresponding conventional crop control measures estimation in region
Irrigate date and irrigation volume.
Because Crops Drought is mainly reflected in cumulative effect, moisture of the water deficit index typically to continuous 5 periods loses
Adactylism number weighted sum：
CWDI=a × CWDIi+b×CWDIi-1+c×CWDIi-2+d×CWDIi-3+e×CWDIi-4
In formula：CWDI is certain section of accumulation Crop water deficits index of time；CWDIi、CWDIi-1、CWDIi-2CWDIi-3、
CWDIi-4The water deficit index of this time and preceding 4 time respectively；A, b, c, d, e are respectively 5 weights of period of the above
Value, typically value is respectively：0.3、0.25、0.2、0.15、0.1.
ET in above formulamCan be calculated using following formula：
ETm=Kc·ET0
In formula：ET0It is the crop reference evapotranspiration of 10 days；KcIt is the crop coefficient of certain crop, it is more complete for data
Monitored area, sets up crop coefficient database, and unconditional region can set up FAO and recommend crop coefficient database or directly fortune
The numerical value that is determined by experiment with neighborhood sets up database.
ET0It is calculated using following formula：
The formula parameter is more, and now the meaning and calculation to each parameter are explained in detail that (what be should be noted is a bit
Required by the formula is daily evapotranspiration rate of referential crops, finally result is sued for peace so as to obtain the accumulated value of 10 days)：
T：Daily mean temperature (DEG C), is obtained, i.e., by the mean value calculation of daily maximum temperature and daily minimal tcmperature：
es：Same day saturation vapour pressure (kPa).The saturation vapour pressure of one day is related to daily temperature is worked as, therefore can use gas
Temperature calculates same day saturation vapour pressure, and calculation is as follows：
The reckoning equation of saturation vapour pressure is nonlinear equation as can be seen from the above equation, therefore uses daily mean temperature direct
Lower result can be caused if solution, therefore the saturation vapour for being calculated using daily maximum temperature and the lowest temperature in the present invention
The average value of pressure：
ea：Same day actual water vapor pressure (kPa), for that can be calculated with following formula with determining the area of relative humidity：
ea=Rh·es
In formula：RhIt is same day average relative humidity (%)；esIt is same day saturation vapour pressure.
Same day actual water vapor pressure can also be tried to achieve using dew-point temperature instead of temperature：
In formula：TdewIt is dew-point temperature (DEG C), that is to say, that actual water vapor pressure is the saturation vapour pressure under dew-point temperature.
Δ：The saturation vapour pressure slope of curve, i.e. saturation vapour pressure with temperature Change speed, that is, above-mentioned reckoning saturation
The derivative value of vapour pressure equation：
In formula：T is temperature (DEG C)；
Rn：Day net radiation amount (MJm-2·d-1).Net radiation amount be obtain solar radiation with reflection solar radiation it
Difference：
Rn=Rns-Rnl
In formula：RnsIt is the net short-wave radiation for obtaining；RnlIt is the long wave net radiation of expenditure.Net short-wave radiation RnsBy receive and
The balance of solar radiation relation of reflection is calculated：
Rns=(1- α) Rs
In formula：RsIt is day solar radiation (MJm-2·d-1)；α is surface albedo, can be with profit for conditional region
More accurate surface albedo is obtained with satellite remote sensing date inverting, conditional can not take green meadow reference crop
Albedo：0.23, and modified according to provincial characteristics；
Long-wave radiation Rnl4 power to earth's surface absolute temperature are related, and by Stefan-Boltzmann constant quantificational expression.
Long wave is also influenceed by factors such as steam, clouds simultaneously in practice, it is therefore desirable to take into account these factors.Given below
Formula allows for humidity and influence of the cloud amount to long-wave radiation, with the addition of two computing formula for correcting the factor：
In formula：TMax, KWith TMin, KRespectively same day highest absolute temperature and minimum absolute temperature, according to K=DEG C+273.16
Relation changed；σ is Stefan-Boltzmann constant, and its value is 4.903 × 10-9MJ K-4m-2day-1；eaIt is actual water
Vapour pressure；RsIt is solar radiation；RsoIt is clear sky solar radiation (MJm-2·d-1)。
Determine clear sky solar radiation RsoThen will definitely outer solar radiation Ra.Extraterrestrial radiation has with geographic latitude and day sequence
Close, can be determined by following formula：
In formula：IscBe solar constant, i.e. 4.921MJ/ (m2·h)；E0It is Eccentricity of the earth correction factor；ω is ground
The angular speed of revolutions, i.e. 0.2618rad/h；TSRIt is sunrise time；δ is the solar declination of Circular measure；φ is the ground of Circular measure
Reason latitude.
Eccentricity of the earth E0Can be calculated with following formula：
In formula：dnIt is day sequence number, takes the serial number 1 in the January 1 of each year, the serial number 365 on December 31 is (to calculate
Convenient acquiescence only 28 days all 2 months, in practice because the presence in leap year can cause certain trueness error, also can be before calculating
Judge whether the time is the leap year so that it is determined that day sequence)；
Solar declination δ can be estimated using below equation：
In formula：dnIt is day sequence number, the implication with equation is identical, the solar declination obtained by calculating is Circular measure, sunrise time
TSRCan be calculated with following formula：
In formula：δ is the solar declination (rad) of Circular measure；φ is the geographic latitude (rad) of Circular measure；ω is earth rotation
Angular speed；
The energy for wanting accurate predicting radiation energy to be lost through air is more difficult, it is assumed here that extraterrestrial radiation is passed through
The loss amount that air reaches ground is 20%, can change the value according to the difference of the estimation result in region and measured result afterwards,
Based on this it is assumed that the possible maximum solar in earth surface certain point：
Rso=0.8 × Ra
In formula：RaIt is solar radiation outside ground；
G：Soil heat flux:Soil heat flux is one relative to net radiation RnFor very little value, especially in earth's surface
During by vegetative coverage, therefore this can omit under less time scale.For moon yardstick soil heat flux, it can be assumed that
It is constant 2.1MJm in appropriate depth of soil, soil heat capacity-3℃-1, then following estimation equation can have been obtained：
G=0.14 (Tmonthi-Tmonthi-1)
In formula：TmonthiIt is the temperature on average of i-th month；Tmonthi-1It is upper monthly mean temperature.u2：Wind at two meters from the ground
Fast (m/s), other are highly observed the wind speed for obtaining and can be corrected using following formula：
In formula：uzIt is the wind speed (m/s) surveyed at z-height；Z is placement height (m) of airspeedometer.γ：Psychrometer is normal
(kPa DEG C of number-1), can be calculated by following formula：
γ=0.665 × 10-3P
In formula：P is atmospheric pressure (kPa)；Z is local height above sea level (m).
Daily crop reference evapotranspiration is obtained according to parameter calculation given above, by the crop set up before
COEFFICIENT KcDatabase can calculate daily Penman-Monteith formula, and crop water this period is calculated using the Penman-Monteith formula of accumulation 10 days
Wane index；
The agricultural arid of the period can be determined according to following standard, and a situation arises：
Wherein, the continuous of S101 is calculated as without effective precipitation (snowfall, accumulated snow) number of days (Dnp)：For not carrying out soil
The region of Soil Moisture Monitoring, it is possible to use continuous this index without effective precipitation replaces relative moisture of the soil Rsm, it is adaptable to which rain supports agriculture
Industry area：
In formula：DnpiPrecipitation Day for intra day ward less than effectiv precipitation；A is season adjustment factor, (March to 5 in spring
Month) it is 1, summer (June to August) is 1.4, and autumn and winter (September to November and December were to 2 months) they are 0.8；
Also season can be divided using mean temperature, i.e., is the summer when waiting 22 DEG C of mean temperature ＞ being within 5 days one to wait
In season, wait 10 DEG C of mean temperature ＜ to be is winter, and it between 10 DEG C~20 DEG C is spring and autumn to wait mean temperature, and 22 are raised to by 10 DEG C
DEG C it is spring, 10 DEG C is dropped to for autumn by 22 DEG C；
Can judge whether the rainfall of a day is effective using following formula：
In formula：P is intra day ward (mm)；P0It it is day effectiv precipitation critical value (mm), generally, in the water of crop
Divide critical period effective precipitation to take 5mm/day, 3mm/day is taken in remaining stage effective precipitation of plant growth；
Be calculated it is continuous be referred to regional standard without effective precipitation number of days and carry out the classification of damage caused by a drought, be with Yunnan Province
Example, arid classification standard is as follows：
Be should be noted during using the index：1st, the index is applied to the dry crop of rain-fed agriculture region；2nd, such as it is in crop
Growth needs water critical zone, continuous should accordingly be expanded without effective precipitation number of days to what is be calculated.
Preferably, the precipitation anomaly percentage of the S101 is calculated as：Precipitation anomaly percentage can characterize some time
Section precipitation more can intuitively reflect the agricultural as caused by Abnormal Precipitation compared with the percentage of Climatological mean situation degree on the low side
Degree of drought, precipitation anomaly percentage grade is suitable for without soil moisture content monitoring, the farming region without water source supply；
Certain period precipitation anomaly percentage (Pa) is calculated as follows：
In formula：P is the precipitation (mm) of certain period；It is the same period average precipitation (mm) of calculation interval；δ is adjusted for season
Section coefficient (division about season has been discussed above), summer is 1.6, and spring is 1, and winter is 0.8.
Wherein, the integrated agriculture drought index of S102 is calculated as：According to monitored area feature and to the area observation data
Grasping level choose These parameters carry out calculate and arid be classified, the arid grade of gained is weighted summation：
In formula：XiIt is i-th drought index for being calculated；piIt is the weight of i-th drought index for being calculated, andAssign all drought indexs equal weight when monitoring and starting, according to the comparison of result and field data
The weighted value of each index is adjusted, the need for it is finally met the regional agriculture draught monitor.
The time (being accurate to every 10 days) and do that can determine that certain point arid in region occurs are calculated by this step
The degree that drought occurs.
Preferably, the S103 is specifically calculated as：For a certain region, its overall degree of drought can have following formula to determine：
In formula：RiIt is the agricultural arid index of certain arid period；A is the total sown area in this area；AiFor occur light drought, in
Non-irrigated, weight drought, the farming region area of special drought；aiIt is light non-irrigated, middle non-irrigated, weight drought, the weight of special drought grade, a is taken here1=5%, a2=
15%, a3=30%, a4=50%.
It is calculated agricultural arid index and is carried out according to the following table arid classification：
According to the classification of the index, the arid for reaching light drought above rank is then judged to that the region occurs agricultural arid, hair
Go out this grade of early warning of arid.
For longer time yardstick, its arid degree can have greatly changed, it is necessary to an index carrys out comprehensive saying
A situation arises and degree for arid in bright this section of period.Time agricultural arid index is comprehensively commented for a certain period agricultural arid intensity
Estimate index.The index can be estimated to more than two drought process, and calculation is as follows：
In formula：Ti is time agricultural arid index；Hop count when T is total；TijFor this when it is disconnected in there is the number of days of arid；aiFor
The weight of each grade arid, respectively 5%, 15%, 30%, 40%.
Time agricultural arid index according to the form below obtained by calculating is classified：
The calculating of three steps, just can determine whether agricultural arid situation of the current region in a certain period more than, dry to agricultural
Drought is estimated.According to national standard, the agricultural arid situation in certain region can be carried out following qualitative description：
1st, agricultural arid is lasting, i.e. the period has occurred agricultural arid, and arid grade a period is equal earlier above.
2nd, there is agricultural arid in agricultural arid development, the i.e. period, and arid grade increased more for the previous period.
3rd, agricultural arid relaxes, i.e. the period has occurred agricultural arid, and arid grade has been reduced more for the previous period.
4th, agricultural arid is released, i.e. the period does not occur agricultural arid, and for the previous period there is arid.
According to regional agriculture arid, a situation arises, and corresponding drought early warning is sent with reference to arid grade, is local agricultural
Production provides arid defensive measure, to reduce the loss that arid is caused.
When setting up the system for a certain region, the basic data in the region should be first collected, and be updated at any time
To ensure to the ageing of the area monitoring.Can be divided into geographical number for the data information that a region carries out agricultural arid monitoring
According to, meteorological data and agricultural data：
1st, geodata：Including monitored area scope, longitude and latitude, height above sea level etc..The warp of the other region weather monitoring website
Latitude is also necessary with height above sea level.
2nd, meteorological data：Etc. the precipitation observed day by day including the region, temperature, wind speed, relative humidity, solar radiation, remove
Recent meteorological data, in addition it is also necessary to the region history meteorological data of at least 30 years, so that the average value for obtaining can be represented
The climatic characteristic in the region.
3rd, agricultural data：The present status of land utilization in the region, land management unit, main long-term cropping, cultivated area, often
Rule Agricultural management system etc..
The foundation of the system needs to be integrated the data of above-mentioned three types so as to the data that cannot directly observe
Calculated.
The foregoing description of the disclosed embodiments, enables professional and technical personnel in the field to realize or uses the present invention.
Various modifications to these embodiments will be apparent for those skilled in the art, herein
Defined General Principle can be realized in other embodiments without departing from the spirit or scope of the present invention.Cause
This, the present invention is not intended to be limited to the embodiments shown herein, and is to fit to and principles disclosed herein and new
The consistent scope most wide of clever feature.
Claims (8)
1. a kind of agricultural arid early warning system, it is characterised in that：Including following steps：
Step one：Unidirectional agricultural arid index is calculated；
(1) Standardized Precipitation index (SPI)
(2) relative moisture of the soil (Rsm)
(3) Crop water deficits index (CWDI)
(4) it is continuous without effective precipitation (snowfall, accumulated snow) number of days (Dnp)
(5) precipitation anomaly percentage
Step 2：Integrated agriculture drought index is calculated：Whether certain puts area in judging region with reference to unidirectional agricultural arid index
Generation arid；
Step 3：Zoning property agricultural drought indices and time agricultural drought indices：Determine agricultural arid occur scope, when
Between, and arid state of development is judged, send corresponding drought early warning.
2. a kind of agricultural arid early warning system as claimed in claim 1, it is characterised in that：The Standardized Precipitation of the step one
Index (SPI) is calculated as：Assuming that the precipitation of a certain period is x, its probability density function for meeting Gamma distributions is：
In formula：α ＞ 0 are form parameter；β ＞ 0 are scale parameter；X ＞ 0 are precipitation, and unit is mm；Γ (α) is distributed for Gamma
Cumulative probability density function, be：
Value on α and β can be adopted and calculate estimate with the following method：
In above formula:xiIt is the sample value of precipitation,It is the average value of precipitation, n is the length of the sequence of calculation.Thus may be used
The cumulative probability of random time length is calculated according to above-mentioned equation g (x)：
Due to the situation not comprising x=0 in Gamma equations, if occurring precipitation in time scale in practice for 0 situation,
Cumulative probability density is calculated using following equations:
H (x)=q+ (1-q) G (x)
In above formula：Q is the probability that precipitation is 0, that is, precipitation is 0 quantity in setting m as precipitation, then have q=m/n；
Normal state treatment is carried out to above-mentioned equation, will the standardized normal distribution letter of the above-mentioned counted probable value substitution of equation institute
Number：
Above formula can be solved using following approximate formula in actual applications：
When 0 ＜ H (x)≤0.5：
As 0.5 ＜ H (x) ＜ 1：
In above formula：C0=2.515517, c1=0.802853, c2=0.010328, d1=1.432788, d2=0.189269,
D3=0.001308.
3. a kind of agricultural arid early warning system as claimed in claim 1, it is characterised in that：The soil of the step one is relatively wet
Degree (Rsm) is calculated as：Relative moisture of the soil is calculated as follows formula：
In formula：Rsm is the average relative moisture of the soil of figure layer；A is Crop development phase adjustment factor, and seedling stage faces for 0.9 crop water
Boundary's phase be 1.1, remaining puberty be 1, pair with parameter a, Relational database can be set up according to region chief crop, it has been determined that
For Different Crop different times a value；wiIt is i-th layer of water content of soil (%)；fciFor the field of i-th layer of soil is held
Water (%)；N is the soil layer number of observation, should be each layer of addition weight by thickness when each soil horizon thickness is different.
4. a kind of agricultural arid early warning system as claimed in claim 1, it is characterised in that：The crop water of the step one loses
Adactylism number (CWDI) is calculated as：The calculation of certain section of Crop water deficits index of time is as follows：
In formula：ETmIt is certain section of Penman-Monteith formula of time (mm), because agricultural arid is lasting water deficit so as to influence plant
One kind arid caused by normal growth, therefore the parameter and remaining parameter take the cumulant of 10 days, calculate the moisture of 10 days
The exponential accumulation that wanes value；PiWith IiThe respectively precipitation and irrigation volume of monitored area section time, as it was previously stated, taking 10 days
Cumulant, if detection zone lacks the monitoring to irrigation volume, can irrigate day by the corresponding conventional crop control measures estimation in region
Phase and irrigation volume；
Because Crops Drought is mainly reflected in cumulative effect, water deficit of the water deficit index typically to continuous 5 periods refers to
Number weighted sum：
CWDI=a × CWDIi+b×CWDIi-1+c×CWDIi-2+d×CWDIi-3+e×CWDIi-4
In formula：CWDI is certain section of accumulation Crop water deficits index of time；CWDIi、CWDIi-1、CWDIi-2CWDIi-3、CWDIi-4
The water deficit index of this time and preceding 4 time respectively；A, b, c, d, e are respectively 5 weighted values of period of the above, typically
Value is respectively：0.3、0.25、0.2、0.15、0.1；
ET in above formulamCan be calculated using following formula：
ETm=Kc·ET0
In formula：ET0It is the crop reference evapotranspiration of 10 days；KcIt is the crop coefficient of certain crop, the monitoring more complete for data
Region, sets up crop coefficient database, and unconditional region can set up FAO and recommend crop coefficient database or directly use to face
Numerical value that near-earth area is determined by experiment sets up database；
ET0It is calculated using following formula：
The formula parameter is more, and now the meaning and calculation to each parameter are explained in detail that (what be should be noted is some the formula
Required is daily evapotranspiration rate of referential crops, finally result is sued for peace so as to obtain the accumulated value of 10 days)：
T：Daily mean temperature (DEG C), is obtained, i.e., by the mean value calculation of daily maximum temperature and daily minimal tcmperature：
es：Same day saturation vapour pressure (kPa).The saturation vapour pressure of one day is related to daily temperature is worked as, therefore can be calculated using temperature
Same day saturation vapour pressure, calculation is as follows：
The reckoning equation of saturation vapour pressure is nonlinear equation as can be seen from the above equation, therefore uses daily mean temperature direct solution
If can cause Lower result, therefore the saturation vapour pressure that is calculated using daily maximum temperature and the lowest temperature in the present invention
Average value：
ea：Same day actual water vapor pressure (kPa), for that can be calculated with following formula with determining the area of relative humidity：
ea=Rh·es
In formula：RhIt is same day average relative humidity (%)；esIt is same day saturation vapour pressure.
Same day actual water vapor pressure can also be tried to achieve using dew-point temperature instead of temperature：
In formula：TdewIt is dew-point temperature (DEG C), that is to say, that actual water vapor pressure is the saturation vapour pressure under dew-point temperature；
Δ：The saturation vapour pressure slope of curve, i.e. saturation vapour pressure with temperature Change speed, that is, above-mentioned reckoning saturation vapour
Press the derivative value of equation：
In formula：T is temperature (DEG C)；
Rn：Day net radiation amount (MJm-2·d-1).Net radiation amount is the difference of the solar radiation of the solar radiation and reflection for obtaining：
Rn=Rns-Rnl
In formula：RnsIt is the net short-wave radiation for obtaining；RnlIt is the long wave net radiation of expenditure.Net short-wave radiation RnsBy receiving and reflecting
Balance of solar radiation relation be calculated：
Rns=(1- α) Rs
In formula：RsIt is day solar radiation (MJm-2·d-1)；α is surface albedo, can be utilized for conditional region and defended
Star remotely-sensed data inverting obtains more accurate surface albedo, does not have the conditional reflection of light that can take green meadow reference crop
Rate：0.23, and modified according to provincial characteristics；
Long-wave radiation Rnl4 power to earth's surface absolute temperature are related, and by Stefan-Boltzmann constant quantificational expression.It is actual
Middle long wave is also influenceed by factors such as steam, clouds simultaneously, it is therefore desirable to take into account these factors.Formula given below
Humidity and influence of the cloud amount to long-wave radiation are allowed for, two computing formula for correcting the factor are with the addition of：
In formula：TMax, KWith TMin, KRespectively same day highest absolute temperature and minimum absolute temperature, according to K=DEG C+273.16 of pass
System is changed；σ is Stefan-Boltzmann constant, and its value is 4.903 × 10-9MJ K-4m-2day-1；eaIt is actual vapor
Pressure；RsIt is solar radiation；RsoIt is clear sky solar radiation (MJm-2·d-1)；
Determine clear sky solar radiation RsoThen will definitely outer solar radiation Ra.Extraterrestrial radiation and geographic latitude and day sequence it is relevant,
Can be determined by following formula：
In formula：IscBe solar constant, i.e. 4.921MJ/ (m2·h)；E0It is Eccentricity of the earth correction factor；ω be the earth from
The angular speed for turning, i.e. 0.2618rad/h；TSRIt is sunrise time；δ is the solar declination of Circular measure；φ is the geographical latitude of Circular measure
Degree；
Eccentricity of the earth E0Can be calculated with following formula：
In formula：dnIt is day sequence number, takes the serial number 1 in the January 1 of each year, the serial number 365 on December 31 is (for convenience of calculation is silent
Recognize all 2 months only 28 days, in practice because the presence in leap year can cause certain trueness error, year can be also judged before calculating
Whether part is the leap year so that it is determined that day sequence)；
Solar declination δ can be estimated using below equation：
In formula：dnIt is day sequence number, the implication with equation is identical, the solar declination obtained by calculating is Circular measure.Sunrise time TSRCan
It is calculated with following formula：
In formula：δ is the solar declination (rad) of Circular measure；φ is the geographic latitude (rad) of Circular measure；ω is the angle of earth rotation
Speed；
The energy for wanting accurate predicting radiation energy to be lost through air is more difficult, it is assumed here that extraterrestrial radiation passes through air
The loss amount for reaching ground is 20%, can change the value according to the difference of the estimation result in region and measured result afterwards.It is based on
This is it is assumed that the possible maximum solar in earth surface certain point：
Rso=0.8 × Ra
In formula：RaIt is solar radiation outside ground；
G：Soil heat flux.Soil heat flux is one relative to net radiation RnFor very little value, especially in earth's surface by vegetation
During covering, therefore this can omit under less time scale, for moon yardstick soil heat flux, it can be assumed that appropriate
Depth of soil, soil heat capacity be constant 2.1MJm-3℃-1, then following estimation equation can have been obtained：
G=0.14 (Tmonthi-Tmonthi-1)
In formula：TmonthiIt is the temperature on average of i-th month；Tmonthi-1It is upper monthly mean temperature.u2：Wind speed (m/ at two meters from the ground
S), other are highly observed the wind speed for obtaining and can be corrected using following formula：
In formula：uzIt is the wind speed (m/s) surveyed at z-height；Z is placement height (m) of airspeedometer.γ：Psychrometer constant (kPa
℃-1), can be calculated by following formula：
γ=0.665 × 10-3P
In formula：P is atmospheric pressure (kPa)；Z is local height above sea level (m).
5. a kind of agricultural arid early warning system as claimed in claim 1, it is characterised in that：The continuous nothing of the step one is effectively
Precipitation (snowfall, accumulated snow) number of days (Dnp) is calculated as：For the region for not carrying out soil moisture content monitoring, it is possible to use continuous nothing
This index of effective precipitation is instead of relative moisture of the soil Rsm, it is adaptable to rain-fed agriculture region：
In formula：DnpiPrecipitation Day for intra day ward less than effectiv precipitation；A is season adjustment factor, and spring (March to May) is
1, summer (June to August) is 1.4, and autumn and winter (September to November and December were to 2 months) are 0.8；
Also season can be divided using mean temperature, i.e., is summer when waiting 22 DEG C of mean temperature ＞ being within 5 days one to wait, waited
It is winter that 10 DEG C of mean temperature ＜ is, it between 10 DEG C~20 DEG C is spring and autumn to wait mean temperature, and being raised to 22 DEG C by 10 DEG C is
In spring, 10 DEG C are dropped to for autumn by 22 DEG C.Can judge whether the rainfall of a day is effective using following formula：
In formula：P is intra day ward (mm)；P0It is day effectiv precipitation critical value (mm), generally, faces in the moisture of crop
Boundary's phase effective precipitation takes 5mm/day, and 3mm/day is taken in remaining stage effective precipitation of plant growth.
6. a kind of agricultural arid early warning system as claimed in claim 1, it is characterised in that：The precipitation anomaly of the step one
Percentage is calculated as：Certain period precipitation anomaly percentage (Pa) is calculated as follows：
In formula：P is the precipitation (mm) of certain period；It is the same period average precipitation (mm) of calculation interval；δ is to adjust system in season
Number (division about season has been discussed above), summer is 1.6, and spring is 1, and winter is 0.8.
7. a kind of agricultural arid early warning system as claimed in claim 1, it is characterised in that：The step 2 integrated agriculture arid
Index is calculated as：Chosen according to monitored area feature and to the Grasping level of the area observation data These parameters calculate and
Arid classification, summation is weighted by the arid grade of gained：
In formula：XiIt is i-th drought index for being calculated；piIt is the weight of i-th drought index for being calculated, andAssign all drought indexs equal weight when monitoring and starting, according to the comparison of result and field data
The weighted value of each index is adjusted, the need for it is finally met the regional agriculture draught monitor；
Time (being accurate to every 10 days) and the arid hair of certain point arid generation in region are can determine that by the calculating of this step
Raw degree.
8. a kind of agricultural arid early warning system as claimed in claim 1, it is characterised in that：The step 3 is specifically calculated as：
For a certain region, its overall degree of drought can have following formula to determine：
In formula：RiIt is the agricultural arid index of certain arid period；A is the total sown area in this area；AiTo there is light non-irrigated, middle drought, weight
The farming region area of drought, special drought；aiIt is light non-irrigated, middle non-irrigated, weight drought, the weight of special drought grade, a is taken here1=5%, a2=15%,
a3=30%, a4=50%；
For longer time yardstick, its arid degree can have greatly changed, it is necessary to an index comprehensively to illustrate this
A situation arises and degree for arid in the section period.Time agricultural arid index refers to for a certain period agricultural arid intensity comprehensive assessment
Mark.The index can be estimated to more than two drought process, and calculation is as follows：
In formula：Ti is time agricultural arid index；Hop count when T is total；TijFor this when it is disconnected in there is the number of days of arid；aiFor each etc.
The weight of level arid, respectively 5%, 15%, 30%, 40%.
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Cited By (13)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107329938A (en) * | 2017-06-29 | 2017-11-07 | 北京师范大学 | A kind of river Droughts situation Forecasting Methodology |
| CN107909301A (en) * | 2017-12-12 | 2018-04-13 | 中国水利水电科学研究院 | A kind of fitness-for-service assessment method of drought index |
| CN108765906A (en) * | 2018-04-11 | 2018-11-06 | 南安市创培电子科技有限公司 | A kind of monitoring of agricultural arid and early alarming and forecasting method |
| CN109596811A (en) * | 2018-12-26 | 2019-04-09 | 武汉大学 | A kind of agricultural arid monitoring method based on Different Soil Water Deficits |
| CN109710598A (en) * | 2018-12-14 | 2019-05-03 | 吉林省中农阳光数据有限公司 | A kind of Meteorological Index insurance system and its implementation based on crops |
| CN110135677A (en) * | 2019-03-27 | 2019-08-16 | 山东省农业可持续发展研究所 | Winter wheat drought remote sensing monitoring grading index system |
| CN110243409A (en) * | 2019-06-18 | 2019-09-17 | 中国农业科学院农业资源与农业区划研究所 | A kind of eco-drought monitoring and forecasting system and method based on earth's surface water-heat process |
| CN110596345A (en) * | 2019-07-29 | 2019-12-20 | 中国水利水电科学研究院 | Computing method for drought and waterlogging sharp turning standard |
| CN112084433A (en) * | 2020-09-14 | 2020-12-15 | 周盛 | Method for carrying out drought resisting operation of artificially influencing weather according to regional division |
| CN112837169A (en) * | 2021-01-11 | 2021-05-25 | 黄河勘测规划设计研究院有限公司 | Gridding drought comprehensive monitoring, early warning and evaluating method in drought process |
| US11313811B2 (en) | 2019-12-27 | 2022-04-26 | International Business Machines Corporation | Dynamic determination of irrigation-related data using machine learning techniques |
| CN114897423A (en) * | 2022-06-06 | 2022-08-12 | 河海大学 | Farmland irrigation probability index calculation method based on crop moisture indicator line |
| CN116384591A (en) * | 2023-05-23 | 2023-07-04 | 中国水利水电科学研究院 | Drought prediction method, system and medium based on big data |
Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR20110066987A (en) * | 2009-12-12 | 2011-06-20 | 주식회사하남엔지니어링 | High-test agricultural integrate remot control system |
-
2017
- 2017-01-17 CN CN201710030252.2A patent/CN106815658A/en active Pending
Patent Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR20110066987A (en) * | 2009-12-12 | 2011-06-20 | 주식회사하남엔지니어링 | High-test agricultural integrate remot control system |
Non-Patent Citations (2)
| Title |
|---|
| 中华人名共和国国家质量监督检验检疫总局和中国国家标准化管理委员会: "《气象干旱等级》", 28 August 2006 * |
| 国家质量监督检验检疫总局: "《农业干旱等级（征求意见稿）》", 8 August 2008 * |
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| CN107329938A (en) * | 2017-06-29 | 2017-11-07 | 北京师范大学 | A kind of river Droughts situation Forecasting Methodology |
| CN107909301A (en) * | 2017-12-12 | 2018-04-13 | 中国水利水电科学研究院 | A kind of fitness-for-service assessment method of drought index |
| CN108765906A (en) * | 2018-04-11 | 2018-11-06 | 南安市创培电子科技有限公司 | A kind of monitoring of agricultural arid and early alarming and forecasting method |
| CN109710598A (en) * | 2018-12-14 | 2019-05-03 | 吉林省中农阳光数据有限公司 | A kind of Meteorological Index insurance system and its implementation based on crops |
| CN109596811A (en) * | 2018-12-26 | 2019-04-09 | 武汉大学 | A kind of agricultural arid monitoring method based on Different Soil Water Deficits |
| CN110135677A (en) * | 2019-03-27 | 2019-08-16 | 山东省农业可持续发展研究所 | Winter wheat drought remote sensing monitoring grading index system |
| CN110243409A (en) * | 2019-06-18 | 2019-09-17 | 中国农业科学院农业资源与农业区划研究所 | A kind of eco-drought monitoring and forecasting system and method based on earth's surface water-heat process |
| CN110596345A (en) * | 2019-07-29 | 2019-12-20 | 中国水利水电科学研究院 | Computing method for drought and waterlogging sharp turning standard |
| US11313811B2 (en) | 2019-12-27 | 2022-04-26 | International Business Machines Corporation | Dynamic determination of irrigation-related data using machine learning techniques |
| CN112084433A (en) * | 2020-09-14 | 2020-12-15 | 周盛 | Method for carrying out drought resisting operation of artificially influencing weather according to regional division |
| CN112084433B (en) * | 2020-09-14 | 2024-04-16 | 周盛 | Method for carrying out weather modification drought-resistant operation according to regional division |
| CN112837169A (en) * | 2021-01-11 | 2021-05-25 | 黄河勘测规划设计研究院有限公司 | Gridding drought comprehensive monitoring, early warning and evaluating method in drought process |
| CN112837169B (en) * | 2021-01-11 | 2024-06-04 | 黄河勘测规划设计研究院有限公司 | Comprehensive monitoring, early warning and evaluating method for gridding drought in drought process |
| CN114897423A (en) * | 2022-06-06 | 2022-08-12 | 河海大学 | Farmland irrigation probability index calculation method based on crop moisture indicator line |
| CN114897423B (en) * | 2022-06-06 | 2023-05-23 | 河海大学 | Farm irrigation probability index calculation method based on crop moisture indication line |
| CN116384591A (en) * | 2023-05-23 | 2023-07-04 | 中国水利水电科学研究院 | Drought prediction method, system and medium based on big data |
| CN116384591B (en) * | 2023-05-23 | 2023-08-29 | 中国水利水电科学研究院 | Drought prediction method, system and medium based on big data |
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