CN109596811A - A kind of agricultural arid monitoring method based on Different Soil Water Deficits - Google Patents
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Abstract
The agricultural arid monitoring method based on Different Soil Water Deficits that the invention discloses a kind of, propose a kind of improved Different Soil Water Deficits agricultural arid Monitoring Index (mSWDI), the index accounts for soil water consumption coefficient and soil shrinkage characteristic, mainly for remote sensing soil moisture product.It includes the following steps: to calculate the remote sensing soil moisture content mean value in a time cycle；Estimate soil moisture content when 33kpa, 1500kpa；Take soil shrinkage characteristic and soil water consumption coefficient into account, water content can be used by calculating soil；In conjunction with soil moisture mean value, field capacity, water content can be used, calculate mSWDI；Agricultural drought extent is judged according to mSWDI score value.The present invention, which accounts for soil caused by the soil shrinkage characteristic that soil caused by dynamic potential evapotranspiration hair and different agrotypes can have with the variation of water content and high clay content, to be over-evaluated with water content, and the room and time scale for monitoring agricultural arid is with more comparativity.
Description
Technical field
The invention belongs to agricultural arid monitoring technical fields, specifically, proposing a kind of improved Different Soil Water Deficits
Agricultural arid Monitoring Index (mSWDI), the index account for soil water consumption coefficient and soil shrinkage characteristic, mainly for remote sensing soil
Earth moisture products are a kind of stronger drought monitoring methods of universality.
Background technique
Traditional agricultural arid monitoring is carried out according to information empty based on meteorological site or monitoring soil moisture website etc.
Interpolation and then the national arid situation of monitoring, are not able to satisfy the assessment and agricultural management of agricultural arid.Remote sensing technology is
China monitors the new development and convenience of agricultural arid bring.
Different Soil Water Deficits caused by being reduced by rainfall are the first characterizations of agricultural arid, and soil moisture lacks, do not fill
The soil moisture of foot supplies plant, will affect the normal growth of plant.So comparing other parameters, soil moisture is one non-
Chang Guanjian and timely factor.Microwave remote sensing technique can detect earth's surface several centimeters down not by inside even from weather
Soil water content, it is very sensitive to the variation of soil moisture.Microwave remote sensing is a kind of of great value Global Scale or area
The monitoring soil moisture tool of domain scale.Meanwhile passive microwave remote sensing has that wide coverage, data processing be simple, the time point
The advantages such as resolution very high (1-3 days), bring soil moisture product abundant, such as SMAP soil moisture product.Wherein, L-band
It has been considered to be that superior soil moisture detecting band has because it can detect the soil moisture at earth's surface 5cm
Relatively high detection accuracy can effectively reflect the spatial variations of soil moisture, be very suitable for the phase based on soil moisture
Close application.In addition, the soil moisture product of high time resolution can also be provided there are many more Model Products, for example, global land
Face data assimilation system (GLDAS).In short, the appearance of a large amount of soil moisture product gives and is based on monitoring soil moisture agricultural arid
Bring opportunity.
Many scholars have begun working on the agricultural arid index based on microwave remote sensing soil moisture, including soil moisture is different
Normal mutation analysis and absolute-value analysis, the drought index research that Soil moisture and temperature vegetation combines, e.g., high-resolution soil
Water deficit index (HSMDI), soil moisture agricultural arid index (SMADI), soil moisture and soil characteristic combine dry
Non-irrigated index research, e.g., soil moisture index (SMI), the soil moisture index (mSMI) of correction, Different Soil Water Deficits index
(SWDI).There are also scholars to combine microwave remote sensing soil moisture with website meteorology driving data progress agricultural arid prediction.Its
In, Different Soil Water Deficits index (SWDI) utilizes the soil moisture and Agro-hydrological Characteristics of Soils (field capacity of dynamic change
With soil wilting coefficient), directly judging whether there is sufficient moisture according to the available soil moisture of root zone can be absorbed by plants, object
It is clear to manage meaning, is comparable on different time scales and space scale, calculating is simple and can be with short cycle Monitoring of Drought
Situation, it is considered to be very valuable drought index.Many scholars are by by SWDI and microwave remote sensing soil moisture product phase
In conjunction with progress agricultural arid study on monitoring.But the available water content of crop is also related with agrotype and soil moisture consumption, separately
Outside, clay content is excessively high, can bring error to available water content valuation.Therefore, SWDI also needs further to develop, and needs to consider
Soil swelling characteristic and soil water consumption factor etc., make it have stronger versatility and draught monitor ability, and space scale has
Stronger comparativity.
Summary of the invention
The present invention provides a kind of Different Soil Water Deficits indexes for taking soil water consumption coefficient and soil shrinkage characteristic into account
(mSWDI), variation and the height of water content can be used by solving soil caused by dynamic potential evapotranspiration hair and different agrotypes
Soil caused by the soil shrinkage characteristic that clay content has can be over-evaluated with water content, can quickly carry out agricultural arid monitoring.
The technical scheme adopted by the invention is that: a kind of agricultural arid monitoring method based on Different Soil Water Deficits provides
One is taken into account the Different Soil Water Deficits index (mSWDI) of soil water consumption coefficient and soil shrinkage characteristic, is suitable for remote sensing soil
Moisture products, specifically includes the following steps:
Step (1) calculates the remote sensing soil moisture data mean value in a time cycle；
Step (2) estimates soil moisture content when 33kpa, 1500kpa；
Step (3) takes soil shrinkage characteristic and soil water consumption coefficient into account, and water content can be used by calculating soil；
Step (4) in conjunction with soil moisture mean value, field capacity, can use water content, the Different Soil Water Deficits of computed improved
Agricultural arid Monitoring Index, is denoted as mSWDI；
Step (5) judges agricultural drought extent according to the mSWDI score value that step (4) obtains.
Further, the soil moisture content in the step (2) when estimation 33kpa, 1500kpa, specific implementation is such as
Under,
In conjunction with soil top layer clay content, husky content and organic carbon content, soil water-containing when 33kpa, 1500kpa is calculated
Amount, calculation formula are as follows:
Wherein, S represents soil top layer sand content, and C represents clay content, and OM represents organic carbon content；θ1500It is 1,500,000
Water content when pa, θ33Water content when being 33 kPas, approximation represents field capacity, and water content is volumetric(al) moisture content.
Further, following sub-step can be specifically included with water content by soil being calculated in step (3):
Step (31) calculates the soil shrinkage factor for the soil shrinkage characteristic of swelled ground, when clay content is greater than 40%
When, part can be over-evaluated with water content to be positively correlated with clay content, it is assumed that over-evaluate part and the linear positive correlation of clay content, because
This, soil shrinkage is as follows because of subformula:
Wherein, q is the soil shrinkage factor, and C is clay content, and γ be that available water content is over-evaluated partially about clay content
Ratio；
Step (32) stops water suction phenomenon in critical moisture content for crop, calculates the soil water consumption factor, and p is soil consumption
Water fugacity, calculation formula are as follows:
Wherein, αpFor regression constant, βpFor regression constant, ET0 is potential evapotranspiration hair, unit cmd-1, NocgFor crop
Type；
Step (33), in conjunction with the soil shrinkage factor and the soil water consumption factor, the available water content of computed improved, formula is such as
Under:
θawc=p (θfc-θwp)=(θ33-θ1500)p/q (11)
Wherein, θ1500Water content when being 1500 kPas, θ33Water content when being 33 kPas.
Further, the specific implementation that mSWDI is calculated in step (4) is as follows,
In conjunction with the soil moisture mean value of step (1)-(3) calculating, field capacity, water content can be used, mSWDI is calculated such as
Under:
MSWDI=10 { [(θ-θfc)/θawc]+1} (12)
Wherein, θ is the soil moisture mean value of a cycle, θfcFor field capacity, θawcFor water content can be used.
Further, step (5) judges that the concrete mode of degree of drought is, is threshold value with 0, mSWDI is indicated greater than 0 can
Soil moisture content is supplied in crop absorption, and arid does not occur；MSWDI is indicated less than 0 can be critical lower than crop with water content
Water content, i.e. generation agricultural arid, and the lower expression damage caused by a drought of score value is more serious.
Compared with prior art, the present invention have following features and the utility model has the advantages that
1, improve index in the applicability in the high region of clay content: swelled ground has soil because clay content is excessively high
Shrinkage character, soil shrinkage lead to that over-evaluating for water content can be used originally, and improved Different Soil Water Deficits index accounts for soil receipts
Contracting characteristic corrects the available water content over-evaluated.
2, improve the precision of Different Soil Water Deficits exponent pair Dry crop draught monitor: soil water consumption factor makes crop exist
Soil moisture content just stops absorbing water when being lower than critical soil moisture content, the addition of soil water consumption coefficient, can hair much sooner
Existing arid crop, reduces underestimating for degree of drought.
3, arid region can be directly judged according to uniform threshold.Improved Different Soil Water Deficits index can substantially determine to be less than
The region of 0 mSWDI covering is the region that arid occurs for high probability, reduces the otherness of different zones drought index threshold value, right
The expression of arid region is apparent.
Detailed description of the invention
Fig. 1 is improved Different Soil Water Deficits index calculation flow chart proposed by the present invention；
Fig. 2 is the soil moisture distribution of mean value figure of the embodiment of the present invention；
Fig. 3 is the soil shrinkage factor distribution map of the embodiment of the present invention；
Fig. 4 is the soil water consumption factor distribution map of the embodiment of the present invention；
Fig. 5 is the mSWDI-SMAP distribution map of the embodiment of the present invention.
Specific embodiment
The present invention will be further described with reference to the accompanying drawings and embodiments.It should be noted that the embodiments described herein is only
For the interpretation present invention, it is not intended to restrict the invention.
The present invention joined the soil shrinkage factor and the soil water consumption factor in Different Soil Water Deficits index, improve soil
Water deficit agricultural arid Monitoring Index, improves draught monitor precision, improves index in space scale and time scale
Comparativity, and it is very convenient quick, it is particularly significant to Drought Prediction early warning.
Step (1): the remote sensing soil moisture data mean value in a time cycle is calculated；
Step (2): soil moisture content when estimation 33kpa, 1500kpa；
Step (3): in conjunction with soil shrinkage characteristic and soil water consumption coefficient, water content can be used by calculating soil；
Step (4): in conjunction with soil moisture mean value, field capacity, water content, the Different Soil Water Deficits of computed improved can be used
Agricultural arid Monitoring Index, is denoted as mSWDI；
Step (5): agricultural drought extent is judged according to the mSWDI score value that step (4) obtains.
It is test area that the embodiment of the present invention, which chooses regional, and input data selects SMAP (Soil Moisture
Active Passive) soil moisture, which takes a large amount of mode and alleviates RFI influence, in the precision phase of regional
To higher, it is more suitable for the research of China's agricultural arid, output is the mSWDI score value based on SMAP soil moisture product, i.e.,
mSWDI-SMAP.In addition, soil top layer clay content, husky content and organic carbon content derive from and are based on world's Soil Database
(HWSD) Chinese soil data set (China Soil Map Based Harmonized World Soil Database
version 1.1).Potential evapotranspiration sends out data from GLDAS product.
Process of the present invention is as shown in Figure 1, comprising the following steps:
Step (1): being the time cycle with one month, calculates the regional SMAP soil moisture mean value in June, 2016, table
Up to for θ, which is volumetric(al) moisture content；
Step (2): soil top layer sand content, clay content, organic carbon content in extraction HWSD, according to formula (1)-
(4), soil moisture content when regional 33kpa, 1500kpa is estimated；Calculation formula is as follows:
Wherein, S represents soil top layer sand content, and C represents clay content, and OM represents organic carbon content.θ1500It is 1,500,000
Water content when pa, θ33Water content when being 33 kPas, approximation represents field capacity herein, and water content is volume of aqueous
Amount.
Step (3): potential evapotranspiration hair, Crop Information, clay content are utilized, in conjunction with soil shrinkage characteristic and soil water consumption system
Number, the available water content of computed improved；
Step (31): for the soil shrinkage characteristic of swelled ground, the soil shrinkage factor is calculated.Clay content is higher to be will cause
It can be over-evaluated with water content.When clay content is greater than 40%, part can be over-evaluated with water content and is positively correlated with clay content, it is assumed that
Over-evaluate part and the linear positive correlation of clay content, therefore, soil shrinkage is as follows because of subformula:
Wherein, q is the soil shrinkage factor, and C is clay content, and γ is that the part of over-evaluating of available water content contains relative to clay
The ratio of amount, here, γ desirable 0.012.
Step (32): stop water suction phenomenon in critical moisture content for crop, calculate the soil water consumption factor.Work as soil water-containing
When amount is less than critical moisture content, crop closes pore, stops water suction, not wilting coefficient.Critical moisture content and agrotype (according to
Divided according to Drought sensitivity) to send out related with potential evapotranspiration, potential evapotranspiration hair is higher, and critical moisture content is lower, and Crops Drought is sensitive
Property is weaker, and critical moisture content is lower, and critical moisture content formula is as follows:
θws=(1-p) (θfc-θwp)+θwp (6)
Wherein, θwsIt is critical moisture content, parameter p is soil moisture consumption part, θfcFor field capacity, θwpWilting system
Number.Therefore, it can obtain:
θawc=θfc-θws=p (θfc-θwp) (7)
Wherein, p is the soil water consumption factor, and calculation formula is as follows:
Wherein, αpFor regression constant, 0.76, β is takenpFor regression constant, take 1.5, ET0 for potential evapotranspiration hair, unit cm
d-1, NocgIt for agrotype, falls into 5 types, value is 1 to 5[1].When agrotype is 1 or 2, the updating formula of p is as follows:
The index studies Arid Problem, and arid region is a variety of to plant the low crop of Drought sensitivity, and a variety of plant of humidification zones is done
The strong crop of non-irrigated sensibility, but humidification zones soil moisture is more sufficient.Therefore, ignore the strong crop of the sensibility of humid region
Draught monitor result is influenced smaller.So soil water consumption factor p simplified formula is as follows under large scale:
Wherein, αpFor regression constant, 0.76, β is takenpFor regression constant, take 1.5, ET0 for potential evapotranspiration hair, unit cm
d-1。NocgDefault value is 5.
[1]Doorenbos,J.,Kassam,A.H.,Bentvelder,C.,Uittenbogaard,G.,1978.Yield
r esponse to water.U.N.Economic Commission West Asia,Rome,Italy.
Step (33): in conjunction with the soil shrinkage factor and the soil water consumption factor, the available water content of computed improved, formula is such as
Under:
θawc=p (θfc-θwp)=(θ33-θ1500)p/q (11)
Step (4): the mSWDI score value based on SMAP, i.e. mSWDI-SMAP score value are calculated.
In conjunction with the soil moisture mean value of step (1)-(3) calculating, field capacity, water content can be used, mSWDI is calculated such as
Under:
MSWDI=10 { [(θ-θfc)/θawc]+1} (12)
Wherein, θ is dynamic soil moisture content, θfcFor field capacity, herein with θ33It is worth equal, θawcIt is aqueous to can be used
Amount.By adding 1 so that 0 for the non-arid of arid of mSWDI separation.
The step (1), the specific steps of embodiment are as follows:
Using ENVI/IDL band math function, the SMAP soil moisture product in June, 2016 of regional is calculated
In each grid average value, be expressed as θ, soil moisture distribution of mean value is as shown in Figure 2.
The step (2), the specific steps of embodiment are as follows:
HWSD product resolution ratio is 1:100 ten thousand, and resampling (aggregation) HWSD data are allowed to spatial resolution and SMAP soil
Moisture data is consistent, and according to formula (1)-(4), calculates the θ of each grid33And θ1500, wherein θ33With field capacity number
It is worth equal.
The step (3) is consumed using potential evapotranspiration hair, Crop Information, clay content in conjunction with soil shrinkage characteristic and soil
Water coefficient, the available water content of computed improved, the specific steps of embodiment are as follows:
Step (31): using the clay content information in HWSD product, judge whether clay content is greater than 40%.If more than
40%, initial value is kept, if being less than or equal to 40%, is assigned a value of 40.Resolution ratio identical with SMAP product is arrived in resampling (aggregation)
(36km) calculates the soil shrinkage factor according to formula (5), and the distribution of the soil shrinkage factor is as shown in Figure 3；
Step (32): the mean value computation soil water consumption factor is sent out using the potential evapotranspiration in June, 2016 of GLDAS product.GLDAS steams
Distributing product space resolution ratio is 0.25 °, carries out bilinearity resampling, is allowed to spatial resolution and SMAP soil moisture product phase
Deng, here, agrotype selects default value 5 (under regional scale, can carry out more fine division) because being national scale,
Emphasis considers the variation that water content can be used caused by potential evapotranspiration hair, calculates the soil water consumption factor, soil consumption according to formula (10)
Water fugacity distribution is as shown in Figure 4.Potential evapotranspiration bill position in GLDAS product is Wm-2With cmd-1Conversion formula such as
Under:
1W·m-2=0.408 × 10-7×3600×24cm·d-1 (13)
Step (33): in conjunction with the soil moisture content of the soil shrinkage factor and the soil water consumption factor and 33kpa, 1500kpa,
Using formula (11), the improved available water content of regional is calculated.
The step (4), the specific steps of embodiment are as follows:
Field capacity (soil when 33kpa of the SMAP soil moisture product, step (2) acquisition that are obtained in conjunction with step (1)
Earth water content), step (3) obtain available water content, calculate the mSWDI based on SMAP soil moisture product, i.e. mSWDI-
SMAP, mSWDI-SMAP distribution are as shown in Figure 5.SMAP soil moisture product is there are deviation, and arid whether judges and degree of drought
Analysis should also be in conjunction with the deviation situation of SMAP product.
The step (5) is in order to judge degree of drought, specific steps are as follows: with 0 is threshold value, mSWDI-SMAP, which is greater than 0, to be indicated
There is available soil moisture content to be supplied in crop absorption, arid does not occur, mSWDI-SMAP indicates to be lower than with water content less than 0
Crop critical moisture content, i.e. generation agricultural arid, and the lower expression damage caused by a drought of score value is more serious.Since SMAP soil moisture product exists
There are dry values deviation, threshold values to adjust to negative value for northern China, there is wet value deviation in south China, and threshold value can be adjusted to positive value
It is whole.
Specific embodiment described herein is only an example for the spirit of the invention.The neck of technology belonging to the present invention
The technical staff in domain can make various modifications or additions to the described embodiments or replace by a similar method
In generation, however, it does not deviate from the spirit of the invention or beyond the scope of the appended claims.
Claims (5)
1. a kind of agricultural arid monitoring method based on Different Soil Water Deficits includes the following steps: it is characterized in that being
Step (1) calculates the remote sensing soil moisture data mean value in a time cycle；
Step (2) estimates soil moisture content when 33kpa, 1500kpa；
Step (3) takes soil shrinkage characteristic and soil water consumption coefficient into account, and water content can be used by calculating soil；
Step (4) in conjunction with soil moisture mean value, field capacity, can use water content, the Different Soil Water Deficits agricultural of computed improved
Draught monitor index, is denoted as mSWDI；
Step (5) judges agricultural drought extent according to the mSWDI score value that step (4) obtains.
2. a kind of agricultural arid monitoring method based on Different Soil Water Deficits according to claim 1, it is characterised in that: institute
Soil moisture content when estimation 33kpa, 1500kpa in step (2) is stated, specific implementation is as follows,
In conjunction with soil top layer clay content, husky content and organic carbon content, soil moisture content when 33kpa, 1500kpa is calculated,
Calculation formula is as follows:
0.027×(C×OM)+0.452(S×C)+0.299 (4)
Wherein, S represents soil top layer sand content, and C represents clay content, and OM represents organic carbon content；θ1500When being 1500 kPas
Water content, θ33Water content when being 33 kPas, approximation represents field capacity, and water content is volumetric(al) moisture content.
3. a kind of agricultural arid monitoring method based on Different Soil Water Deficits according to claim 1, it is characterised in that: step
Suddenly following sub-step can be specifically included with water content by soil being calculated in (3):
Step (31) calculates the soil shrinkage factor for the soil shrinkage characteristic of swelled ground, when clay content is greater than 40%,
Part can be over-evaluated with water content to be positively correlated with clay content, it is assumed that over-evaluate part and the linear positive correlation of clay content, therefore,
Soil shrinkage is as follows because of subformula:
Wherein, q is the soil shrinkage factor, and C is clay content, and γ be that available water content over-evaluates the partially ratio about clay content
Value；
Step (32), for crop critical moisture content stop water suction phenomenon, calculate the soil water consumption factor, p be soil water consumption because
Son, calculation formula are as follows:
Wherein, αpFor regression constant, βpFor regression constant, ET0 is potential evapotranspiration hair, unit cmd-1, NocgTo make species
Type；
Step (33), in conjunction with the soil shrinkage factor and the soil water consumption factor, the available water content of computed improved, formula is as follows:
θawc=p (θfc-θwp)=(θ33-θ1500)p/q (11)
Wherein, θ1500Water content when being 1500 kPas, θ33Water content when being 33 kPas.
4. a kind of agricultural arid monitoring method based on Different Soil Water Deficits, feature described according to claim 1 with 2 and 3
Be: the specific implementation that mSWDI is calculated in step (4) is as follows,
In conjunction with the soil moisture mean value of step (1)-(3) calculating, field capacity, water content can be used, mSWDI calculates as follows:
MSWDI=10 { [(θ-θfc)/θawc]+1} (12)
Wherein, θ is the soil moisture mean value of a cycle, θfcFor field capacity, θawcFor water content can be used.
5. a kind of agricultural arid monitoring method based on Different Soil Water Deficits according to claim 1, it is characterised in that: step
Suddenly (5) judge that the concrete mode of degree of drought is, are threshold value with 0, mSWDI, which is greater than 0, indicates available soil moisture content supply
It is absorbed in crop, arid does not occur；MSWDI indicates that crop critical moisture content can be lower than with water content less than 0, that is, agricultural occurs and does
Drought, and the lower expression damage caused by a drought of score value is more serious.
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| CN110646587A (en) * | 2019-09-29 | 2020-01-03 | 武汉大学 | High-resolution agricultural drought monitoring method and device combining multi-source remote sensing data |
| CN110781259A (en) * | 2019-09-18 | 2020-02-11 | 河海大学 | Hydrological model based on landform unit line |
| CN112730465A (en) * | 2020-12-09 | 2021-04-30 | 中国电建集团华东勘测设计研究院有限公司 | Agricultural drought monitoring method for SMAP L waveband brightness temperature |
| CN113406305A (en) * | 2021-06-29 | 2021-09-17 | 吉林大学 | Agricultural drought monitoring index determination method and system |
| CN113919146A (en) * | 2021-09-28 | 2022-01-11 | 河北地质大学 | Agricultural drought index construction method based on soil quick-acting water |
| CN116229285A (en) * | 2023-05-06 | 2023-06-06 | 深圳大学 | Soil water content monitoring method integrating Internet of things data and space scene |
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