CN109596811B - Agricultural drought monitoring method based on soil water shortage - Google Patents

Agricultural drought monitoring method based on soil water shortage Download PDF

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CN109596811B
CN109596811B CN201811599653.0A CN201811599653A CN109596811B CN 109596811 B CN109596811 B CN 109596811B CN 201811599653 A CN201811599653 A CN 201811599653A CN 109596811 B CN109596811 B CN 109596811B
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孟令奎
白珏莹
张文
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Abstract

The invention discloses an agricultural drought monitoring method based on soil water deficit, and provides an improved agricultural drought monitoring index (mSDDI) for soil water deficit, wherein the index takes into account a soil water consumption coefficient and soil shrinkage characteristics and mainly aims at remote sensing soil water products. Which comprises the following steps: calculating the average value of the moisture content of the remote sensing soil in a time period; estimating the water content of the soil at 33kpa and 1500 kpa; considering the soil shrinkage characteristic and the soil water consumption coefficient, and calculating the available water content of the soil; calculating mSDDI by combining the average value of soil moisture, the field water capacity and the available water content; and judging the agricultural drought degree according to the mWDI value. The invention considers the variation of the available water content of the soil caused by dynamic potential evapotranspiration and different crop types and the overestimation of the available water content of the soil caused by the soil shrinkage characteristic of the high clay content, so that the space and time scale of agricultural drought monitoring are more comparable.

Description

Agricultural drought monitoring method based on soil water shortage
Technical Field
The invention belongs to the technical field of agricultural drought monitoring, and particularly provides an improved soil water deficit agricultural drought monitoring index (mWDI), which considers the soil water consumption coefficient and the soil shrinkage characteristic, is mainly used for remote sensing soil water products, and is a drought monitoring method with stronger universality.
Background
The traditional agricultural drought monitoring is based on meteorological sites or soil moisture monitoring sites and the like, and carries out spatial interpolation according to point information so as to monitor the national drought condition, so that the agricultural drought assessment and agricultural management cannot be met. The appearance of remote sensing technology brings new development and convenience for the agricultural drought monitoring in China.
Soil water deficit caused by reduced rainfall is the first indicator of drought in agriculture, and soil water deficit, insufficient soil water supply to plants, will affect the normal growth of plants. Therefore, soil moisture is a very critical and timely factor compared to other parameters. The microwave remote sensing technology is not influenced by weather factors, can detect the soil moisture content of a few centimeters below the earth surface, and is very sensitive to the change of the soil moisture. Microwave remote sensing is a valuable global or regional scale soil moisture monitoring tool. Meanwhile, passive microwave remote sensing has the advantages of wide coverage range, simple data processing, high time resolution (1-3 days) and the like, and brings abundant soil moisture products, such as SMAP soil moisture products. The L waveband is considered as the most optimal soil moisture detection waveband, and the soil moisture detection waveband can detect soil moisture at 5cm of the ground surface, has relatively high detection precision, can effectively reflect the spatial change of the soil moisture, and is very suitable for related applications based on the soil moisture. In addition, there are also many model products that can provide high time resolution soil moisture products, such as the global terrestrial data assimilation system (GLDAS). In a word, the emergence of a large number of soil moisture products has brought a chance to monitor agricultural drought based on soil moisture.
Many scholars have begun studying agricultural drought indices based on microwave remote sensing of soil moisture, including soil moisture anomaly change analysis and absolute value analysis, soil moisture and temperature vegetation combined drought index studies, e.g., high resolution soil moisture deficit index (HSMDI), Soil Moisture Agricultural Drought Index (SMADI), soil moisture and soil characteristics combined drought index studies, e.g., Soil Moisture Index (SMI), corrected soil moisture index (mSMI), soil moisture deficit index (SWDI). And the learners combine the microwave remote sensing soil moisture with the site meteorological driving data to predict the agricultural drought. The Soil Water Deficit Index (SWDI) utilizes dynamically changed soil water and soil agricultural hydrological characteristics (field water capacity and soil wilting coefficient), whether sufficient water can be absorbed by plants is judged directly according to available soil water in a root zone, the physical significance is clear, the index is comparable on different time scales and space scales, the calculation is simple, the drought condition can be monitored in a short period, and the index is regarded as a valuable drought index. Many scholars have conducted agricultural drought monitoring studies by combining SWDI with microwave remote sensing of soil moisture products. However, the available moisture content of a crop is also related to the type of crop and soil water consumption, and in addition, too high a clay content can introduce errors into the estimation of available moisture content. Therefore, the SWDI needs to be further developed, and needs to consider the soil swelling characteristics, the soil water consumption factors and the like, so that the SWDI has stronger universality and drought monitoring capability, and has stronger comparability on a spatial scale.
Disclosure of Invention
The invention provides a soil water deficit index (mSDDI) considering the water consumption coefficient and the soil shrinkage characteristic of soil, solves the problem of the change of the available water content of the soil caused by dynamic potential evapotranspiration and different crop types and the problem of the overestimation of the available water content of the soil caused by the soil shrinkage characteristic of high-viscosity soil content, and can quickly carry out agricultural drought monitoring.
The technical scheme adopted by the invention is as follows: an agricultural drought monitoring method based on soil water deficit provides a soil water deficit index (mSDDI) taking account of a soil water consumption coefficient and soil shrinkage characteristics, is suitable for remote sensing soil water products, and specifically comprises the following steps:
step (1), calculating a remote sensing soil water data mean value in a time period;
estimating the water content of the soil at 33kpa and 1500 kpa;
step (3), considering the soil shrinkage characteristic and the soil water consumption coefficient, and calculating the available water content of the soil;
step (4), calculating an improved soil water deficit agricultural drought monitoring index by combining the soil water mean value, the field water capacity and the available water content, and recording the improved soil water deficit agricultural drought monitoring index as mWDI;
and (5) judging the agricultural drought degree according to the mWDI value obtained in the step (4).
Further, the soil moisture content at 33kpa and 1500kpa is estimated in the step (2), and the concrete implementation manner is as follows,
and (3) calculating the water content of the soil at 33kpa and 1500kpa by combining the clay content, the sand content and the organic carbon content of the top layer of the soil, wherein the calculation formula is as follows:
Figure BDA0001922139430000021
Figure BDA0001922139430000022
Figure BDA0001922139430000023
Figure BDA0001922139430000024
wherein S represents the top sand content of the soil, C represents the clay content, and OM represents the organic carbon content; theta1500Water content at 1500kPa, theta33The water content at 33kpa, approximately represents field capacity, and is the volumetric water content.
Further, the step (3) of calculating the available water content of the soil specifically comprises the following substeps:
step (31), calculating a soil shrinkage factor according to the soil shrinkage characteristic of the swelling soil, wherein when the clay content is more than 40%, the available water content overestimated part is in positive correlation with the clay content, and the overestimated part is assumed to be in positive linear correlation with the clay content, so that the soil shrinkage factor formula is as follows:
Figure BDA0001922139430000031
wherein q is a soil shrinkage factor, C is a clay content, and gamma is a ratio of an overestimated portion of available water content to the clay content;
step (32), calculating a soil water consumption factor aiming at the phenomenon that the crop stops absorbing water at the critical water content, wherein p is the soil water consumption factor, and the calculation formula is as follows:
Figure BDA0001922139430000032
wherein, αpAs a regression constant, βpFor regression constants, ET0 is the potential evapotranspiration in cm d-1，NocgIs a crop type;
and (33) calculating the improved available water content by combining the soil shrinkage factor and the soil water consumption factor, wherein the formula is as follows:
θawc＝p(θfc-θwp)＝(θ33-θ1500)p/q (11)
wherein, theta1500Water content at 1500kPa, theta33A water content of 33 kPa.
Further, the specific implementation manner of calculating mWDI in the step (4) is as follows,
and (4) combining the soil moisture mean value, the field water capacity and the available water content calculated in the steps (1) to (3), and calculating mSDDI as follows:
mSWDI＝10{[(θ-θfc)/θawc]+1} (12)
wherein theta is the soil water average value of one period, and thetafcIs field water capacity, thetaawcIs the available moisture content.
Further, the specific way of judging the drought degree in the step (5) is that by taking 0 as a threshold value, mSDDI greater than 0 indicates that the available soil water content is supplied to crops for absorption, and no drought occurs; an mSDDI of less than 0 indicates that the available moisture content is below the critical moisture content of the crop, i.e. agricultural drought occurs, and a lower score indicates more severe drought.
Compared with the prior art, the invention has the following characteristics and beneficial effects:
1. the applicability of the index in the region with high clay content is improved: the expansive soil has soil shrinkage characteristics due to overhigh clay content, the soil shrinkage results in overestimation of the original available water content, the improved soil water deficit index takes the soil shrinkage characteristics into consideration, and the overestimated available water content is corrected.
2. The precision of the soil water deficit index on drought monitoring of the dry crops is improved: the water consumption factor of the soil ensures that the crops stop absorbing water when the water content of the soil is lower than the critical water content of the soil, and the addition of the water consumption coefficient of the soil can discover the drought crops more timely and reduce the underestimation of the drought degree.
3. The drought area can be directly judged according to the unified threshold value. The improved soil water deficit index can generally judge that the region covered by the mSDDI smaller than 0 is a region with high probability of drought, reduce the difference of drought index thresholds of different regions and make expression of the drought region clearer.
Drawings
FIG. 1 is a flow chart of improved soil water deficit index calculation proposed by the present invention;
FIG. 2 is a graph of a soil water mean distribution according to an embodiment of the present invention;
FIG. 3 is a soil shrinkage factor profile of an embodiment of the present invention;
FIG. 4 is a soil water consumption factor profile of an embodiment of the present invention;
FIG. 5 is a mSDDI-SMAP profile of an embodiment of the present invention.
Detailed Description
The invention is further explained below with reference to the drawings and the embodiments. It should be noted that the embodiments described herein are only for illustrating the present invention and are not to be construed as limiting the present invention.
According to the method, the soil shrinkage factor and the soil water consumption factor are added into the soil water deficit index, the soil water deficit agricultural drought monitoring index is improved, the drought monitoring precision is improved, the comparability of the index in a space scale and a time scale is improved, and the method is very convenient and rapid and is very important for drought forecast early warning.
Step (1): calculating the average value of remote sensing soil water data in a time period;
step (2): estimating the water content of the soil at 33kpa and 1500 kpa;
and (3): calculating the available water content of the soil by combining the soil shrinkage characteristic and the soil water consumption coefficient;
and (4): calculating an improved soil water deficit agricultural drought monitoring index by combining the soil water mean value, the field water capacity and the available water content, and recording the index as mWDI;
and (5): and (5) judging the agricultural drought degree according to the mWDI value obtained in the step (4).
The embodiment of the invention selects a Chinese area as a test area, inputs data and selects SMAP (soil moisture active passive) soil moisture, the product relieves RFI influence in a large amount of ways, has relatively higher precision in the Chinese area, is more suitable for agricultural drought research in China, and outputs mSDDI (sampled near infrared) value based on SMAP soil moisture products, namely mSDI-SMAP. In addition, the Soil top clay content, sand content and organic carbon content were derived from the chinese Soil data set (China Soil Map Based modified World Soil database 1.1) Based on the World Soil database (HWSD). Potential evapotranspiration data was from the GLDAS product.
The process of the invention is shown in figure 1 and comprises the following steps:
step (1): calculating the average value of SMAP soil water in the Chinese region of 2016 and 6 months by taking one month as a time period, wherein the expression is theta, and the water content is volume water content;
step (2): extracting the sand content, the clay content and the organic carbon content of the top layer of the soil in the HWSD, and estimating the water content of the soil in 33kpa and 1500kpa areas in China according to the formulas (1) to (4); the calculation formula is as follows:
Figure BDA0001922139430000051
Figure BDA0001922139430000052
Figure BDA0001922139430000053
Figure BDA0001922139430000054
wherein S represents the top sand content of the soil, C represents the clay content, and OM represents the organic carbon content. Theta1500Water content at 1500kPa, theta33A moisture content of 33kpa, which here approximately represents field capacity, and is the volumetric moisture content.
And (3): calculating an improved available water content by utilizing the potential evapotranspiration, the crop information and the clay content in combination with the soil shrinkage characteristic and the soil water consumption coefficient;
step (31): and calculating the soil shrinkage factor according to the soil shrinkage characteristics of the expansive soil. Higher clay levels result in an overestimation of the available water content. When the clay content is greater than 40%, the overestimated fraction of available water content is positively correlated with clay content, assuming that the overestimated fraction is linearly and positively correlated with clay content, and therefore, the soil shrinkage factor equation is as follows:
Figure BDA0001922139430000055
where q is the soil shrinkage factor, C is the clay content, and γ is the ratio of the overestimated fraction of available water content to clay content, where γ may be 0.012.
Step (32): and calculating the soil water consumption factor aiming at the phenomenon that the crop stops absorbing water at the critical water content. When the water content of the soil is less than the critical water content, the pores of the crops are closed, water absorption is stopped, and the water is not a wilting coefficient. The critical moisture content is related to the crop type (classified according to drought sensitivity) and the potential evapotranspiration, the higher the potential evapotranspiration, the lower the critical moisture content, the weaker the drought sensitivity of the crop, and the lower the critical moisture content, and the critical moisture content formula is as follows:
θws＝(1-p)(θfc-θwp)+θwp(6)
wherein, thetawsIs the critical water content, the parameter p is the water-consuming part of the soil, θfcIs field water capacity, thetawpA wilting coefficient. Thus, it is possible to obtain:
θawc＝θfc-θws＝p(θfc-θwp) (7)
wherein p is a soil water consumption factor, and the calculation formula is as follows:
Figure BDA0001922139430000061
wherein, αpAs a regression constant, take 0.76, βpTo obtain a regression constant, 1.5 ET0 was taken as the potential evapotranspiration in cm d-1，NocgIs classified into 5 types, and the value is 1 to 5[1]. When the crop type is 1 or 2, the correction formula for p is as follows:
Figure BDA0001922139430000062
the index is used for researching the drought problem, crops with low drought sensitivity are planted in a drought area, crops with high drought sensitivity are planted in a humid area, and soil moisture in the humid area is sufficient. Therefore, ignoring the highly sensitive crops in wet areas has less impact on drought monitoring results. Therefore, on a large scale, the simplified formula of the soil water consumption factor p is as follows:
Figure BDA0001922139430000063
wherein, αpAs a regression constant, take 0.76, βpTo obtain a regression constant, 1.5 ET0 was taken as the potential evapotranspiration in cm d-1。NocgThe default value is 5.
[1]Doorenbos,J.,Kassam,A.H.,Bentvelder,C.,Uittenbogaard,G.,1978.Yieldr esponse to water.U.N.Economic Commission West Asia,Rome,Italy.
Step (33): and calculating the improved available water content by combining the soil shrinkage factor and the soil water consumption factor, wherein the formula is as follows:
θawc＝p(θfc-θwp)＝(θ33-θ1500)p/q (11)
and (4): the mSDDI-based SMAP score, i.e., mSDI-SMAP score, is calculated.
And (4) combining the soil moisture mean value, the field water capacity and the available water content calculated in the steps (1) to (3), and calculating mSDDI as follows:
mSWDI＝10{[(θ-θfc)/θawc]+1} (12)
wherein theta is the dynamic soil moisture content and thetafcFor field water capacity, here with theta33Equal value of thetaawcIs the available moisture content. By adding 1, 0 is made to be the boundary point of drought and non-drought of mSDDI.
In the step (1), the specific steps of the embodiment are as follows:
by utilizing the ENVI/IDL band operation function, the average value of each grid in SMAP soil moisture products of 2016, 6 months in China is calculated and expressed as theta, and the soil moisture average value distribution is shown in figure 2.
In the step (2), the specific steps of the embodiment are as follows:
the resolution of the HWSD product is 1:100 ten thousand, the HWSD data is resampled (gathered) to ensure that the spatial resolution is consistent with the SMAP soil water data, and theta of each grid is calculated according to the formulas (1) - (4)33And theta1500Wherein, theta33Equal to the field water holding capacity value.
In the step (3), the potential evapotranspiration, the crop information and the clay content are utilized, the soil shrinkage characteristic and the soil water consumption coefficient are combined, and the improved available water content is calculated, wherein the specific steps of the embodiment are as follows:
step (31): and judging whether the clay content is more than 40% by using the clay content information in the HWSD product. If the value is more than 40%, the original value is maintained, and if the value is less than or equal to 40%, the value is assigned to 40. Resampling (aggregating) to the same resolution (36km) as the SMAP product, and calculating the soil shrinkage factor according to the formula (5), wherein the soil shrinkage factor distribution is shown in FIG. 3;
step (32): and calculating the soil water consumption factor by using the potential evapotranspiration mean value of the GLDAS product in 2016 and 6 months. The spatial resolution of the GLDAS evapotranspiration product is 0.25 degrees, bilinear resampling is carried out, the spatial resolution is equal to that of the SMAP soil moisture product, here, due to the national scale, the crop type is selected to be a default value of 5 (under the regional scale, finer division can be carried out), the change of available water content caused by potential evapotranspiration is mainly considered, the soil water consumption factor is calculated according to a formula (10), and the distribution of the soil water consumption factor is shown in figure 4. The unit of potential evapotranspiration in GLDAS products is W.m-2And cm.d-1The conversion formula of (c) is as follows:
1W·m-2＝0.408×10-7×3600×24cm·d-1(13)
step (33): the improved available water content in the Chinese area is calculated by combining the soil shrinkage factor and the soil water consumption factor and the soil water content of 33kpa and 1500kpa by using the formula (11).
In the step (4), the specific steps of the embodiment are as follows:
and (3) calculating mSDDI (mSDDI-SMAP) based on the SMAP soil moisture product by combining the SMAP soil moisture product obtained in the step (1), the field moisture capacity (soil moisture content at 33 kpa) obtained in the step (2) and the available moisture content obtained in the step (3), wherein the mSDDI-SMAP distribution is shown in figure 5. The deviation of SMAP soil moisture products exists, and the judgment of drought or not and the analysis of the drought degree are combined with the deviation condition of the SMAP products.
In order to judge the drought degree in the step (5), the specific steps are as follows: and with the threshold value of 0, the mWDI-SMAP is more than 0, which indicates that the available soil moisture content is supplied for the crop to absorb, no drought occurs, the mWDI-SMAP is less than 0, which indicates that the available moisture content is lower than the critical moisture content of the crop, namely, agricultural drought occurs, and the lower the score, the more serious the drought is. As the SMAP soil moisture product has dry value deviation in the north of China, the threshold value can be adjusted to a negative value, and the SMAP soil moisture product has wet value deviation in the south of China, and the threshold value can be adjusted to a positive value.
The specific embodiments described herein are merely illustrative of the spirit of the invention. Various modifications or additions may be made to the described embodiments or alternatives may be employed by those skilled in the art without departing from the spirit or ambit of the invention as defined in the appended claims.

Claims (4)

1. An agricultural drought monitoring method based on soil water deficit is characterized by comprising the following steps:
step (1), calculating a remote sensing soil water data mean value in a time period;
estimating the water content of the soil at 33kpa and 1500 kpa;
step (3), considering the soil shrinkage characteristic and the soil water consumption coefficient, and calculating the available water content of the soil;
the step (3) of calculating the available water content of the soil specifically comprises the following substeps:
step (31), calculating a soil shrinkage factor according to the soil shrinkage characteristic of the swelling soil, wherein when the clay content is more than 40%, the available water content overestimated part is in positive correlation with the clay content, and the overestimated part is assumed to be in positive linear correlation with the clay content, so that the soil shrinkage factor formula is as follows:
Figure FDA0002383667520000011
wherein q is a soil shrinkage factor, C is a clay content, and gamma is a ratio of an overestimated portion of available water content to the clay content;
step (32), calculating a soil water consumption factor aiming at the phenomenon that the crop stops absorbing water at the critical water content, wherein p is the soil water consumption factor, and the calculation formula is as follows:
Figure FDA0002383667520000012
wherein, αpAs a regression constant, βpFor regression constants, ET0 is the potential evapotranspiration in cm d-1，NocgIs a crop type;
and (33) calculating the improved available water content by combining the soil shrinkage factor and the soil water consumption factor, wherein the formula is as follows:
θawc＝p(θfc-θwp)＝(θ33-θ1500)p/q (11)
wherein, theta1500Water content at 1500kPa, theta33A water content of 33 kPa;
step (4), calculating an improved soil water deficit agricultural drought monitoring index by combining the soil water mean value, the field water capacity and the available water content, and recording the improved soil water deficit agricultural drought monitoring index as mWDI;
and (5) judging the agricultural drought degree according to the mWDI value obtained in the step (4).
2. The soil water deficit-based agricultural drought monitoring method according to claim 1, characterized by: the soil water content at 33kpa and 1500kpa is estimated in the step (2), and the concrete implementation mode is as follows,
and (3) calculating the water content of the soil at 33kpa and 1500kpa by combining the clay content, the sand content and the organic carbon content of the top layer of the soil, wherein the calculation formula is as follows:
Figure FDA0002383667520000021
Figure FDA0002383667520000022
Figure FDA0002383667520000023
Figure FDA0002383667520000024
wherein S represents the top sand content of the soil, C represents the clay content, and OM represents the organic carbon content; theta1500Water content at 1500kPa, theta33The water content at 33kpa, approximately represents field capacity, and is the volumetric water content.
3. The soil water deficit-based agricultural drought monitoring method according to claim 1, characterized by: the specific implementation of calculating the mSWDI in step (4) is as follows,
and (4) combining the soil moisture mean value, the field water capacity and the available water content calculated in the steps (1) to (3), and calculating mSDDI as follows:
Figure FDA0002383667520000025
wherein theta is the soil water average value of one period, and thetafcIs field water capacity, thetaawcIs the available moisture content.
4. The soil water deficit-based agricultural drought monitoring method according to claim 1, characterized by: the specific mode of judging the drought degree in the step (5) is that when 0 is taken as a threshold value, mWDI is more than 0, which indicates that the available soil water content is supplied to crops for absorption, and no drought occurs; an mSDDI of less than 0 indicates that the available moisture content is below the critical moisture content of the crop, i.e. agricultural drought occurs, and a lower score indicates more severe drought.
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