CN110599360A - High-resolution remote sensing estimation method for evapotranspiration of crops in arid region - Google Patents
High-resolution remote sensing estimation method for evapotranspiration of crops in arid region Download PDFInfo
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Abstract
The invention relates to a high-resolution remote sensing estimation method for crop growth season evapotranspiration in an arid region, which is used for calculating the high-resolution crop growth season evapotranspiration in the arid region based on time sequence remote sensing data. Estimating the instantaneous evapotranspiration of the crops by using an SEBAL model based on time sequence remote sensing data, and expanding the instantaneous evapotranspiration by using a sine function method to obtain daily evapotranspiration; and further combining the change rule of the crop growth season evapotranspiration to carry out time scale expansion on the daily evapotranspiration to obtain the evapotranspiration of the whole growth season of the crops. The invention overcomes the problem that the daily-scale crop evapotranspiration estimation can only be carried out based on the high-resolution remote sensing technology at present, realizes the extension of the daily scale to the growth season scale, solves the problem of the evapotranspiration remote sensing estimation of the growth season, and provides effective method reference for accurately acquiring the crop growth season evapotranspiration, scientifically managing farmland irrigation, accurately estimating the crop yield and optimizing the configuration of water resources.
Description
Technical Field
The invention relates to the technical field of estimation of evapotranspiration of crops in an arid region based on a remote sensing technology, in particular to a high-resolution remote sensing estimation method of evapotranspiration of crops in the arid region.
Background
The method can timely and accurately acquire the evapotranspiration of crops in the growing season, and can provide effective reference basis for scientific management of farmland irrigation, accurate estimation of crop yield and optimal allocation of water resources.
The traditional methods for estimating and actually measuring evapotranspiration, such as a hydrology method, a micrometeorology method, a plant physiology method, an evapotranspiration instrument method and the like, are mostly based on local area dimensions, and are difficult to apply to a large area range due to the limitation of manpower and material resources. The appearance of the remote sensing technology utilizes the characteristics of time-space continuity and large span of the remote sensing technology, overcomes the difficult problem that fixed-point observation is difficult to popularize to a large area in the traditional research, and solves the problem of evapotranspiration space scale expansion. However, instantaneous information is provided by remote sensing, the current research only extends to the daily scale, and how to extend the daily evapotranspiration to the growing season of crops becomes a difficulty of remote sensing application, and related research reports are not yet seen.
Disclosure of Invention
In view of the above, the present invention aims to provide a high-resolution remote sensing estimation method for crop growth season evapotranspiration in an arid region, which can timely and accurately acquire the crop growth season evapotranspiration.
In order to achieve the purpose, the invention adopts the following technical scheme:
a high-resolution remote sensing estimation method for evapotranspiration of crops in arid regions comprises the following steps:
step S1: acquiring multi-temporal high-resolution remote sensing images of crop growth seasons in a research area, acquiring conventional meteorological observation data, and collecting DEM data in the research area;
step S2: extracting crop planting information from the multi-temporal high-resolution remote sensing image to obtain crop distribution data of a research area;
step S3, constructing an SEBAL model according to crop distribution data in a research area, conventional meteorological observation data and DEM data in the research area;
step S4: calculating the instantaneous evapotranspiration of the remote sensing image acquisition time of the agricultural area based on the SEBAL model;
step S5: expanding the instantaneous evapotranspiration to daily evapotranspiration by a sine function method;
step S6: and performing time scale expansion estimation on the daily evapotranspiration based on the change rule of the crop growth season evapotranspiration to obtain the spatial distribution of the crop growth season evapotranspiration in the agricultural region.
Further, the normal meteorological observation data include daily average air temperature (° c), precipitation amount (mm), relative humidity (%), and wind speed (m/s).
Further, the step S4 is specifically:
step S41: calculating the net surface radiant flux RnThe calculation formula is as follows:
Rn＝(1-α)Rs↓+RL↓-RL↑-(1-ε0)RL↓；
wherein α is the ground surface albedo, Rs↓ is solar short wave radiation incident to the earth surface, RL↓ is incident long wave radiation, RL×) is reflected long wave radiation; epsilon0Is the surface emissivity.
Step S42, calculating the soil heat flux G according to the following formula:
in the formula, TsIs the surface temperature, alpha is the surface albedo, NDVI is the normalized vegetation index, c11Is a satellite correction coefficient, and the transit time is 0.9 before 12 points at the local time and 1.0 between 12 points and 14 points.
Step S43, calculating the soil heat flux H according to the following formula:
in the formula, ρairIs the density of air, CpIs the specific heat of air at constant pressure, dT is the height Z from the ground1And Z2Temperature difference of (d) ofabIs the aerodynamic impedance.
Step S44, the earth surface radiation flux RnThe soil heat flux G and the sensible heat flux H are introduced into an energy balance equation to calculate the latent heat flux lambda ET at the satellite transit time, and the specific calculation formula is as follows:
Rn＝G+H+λET；
in the formula, RnIs the net radiant flux (J.m)-2·s-1) (ii) a G is the soil heat flux (J.m)-2·s-1) (ii) a H is sensible heat flux (J.m)-2·s-1) (ii) a λ ET is the latent heat flux (J · m) at the satellite transit time-2·s-1)。
Step S45: calculating instant evapotranspiration ET of satellite transit time by using latent heat flux lambda ET obtained by calculationinstThe specific calculation formula is as follows:
λ＝(2.501-0.002361×(TS-273.15))×106；
in the formula, ETinstIs an instantaneous evaporation method (J.m)-2·s-1) (ii) a Lambda is latent heat of vaporization (J.m)-2·s-1)。
Further, the step S5 is specifically: estimating the daily evapotranspiration by the aid of a sine function according to the instantaneous evapotranspiration, wherein the specific calculation formula is as follows:
in the formula, NEThe number of evapotranspiration per day, t is the time interval from sunrise to satellite transit time, ETdailyFor daily evapotranspiration, ETinstIs an instant evapotranspiration.
Further, the step S6 is specifically:
step S61: the evapotranspiration change rule of the crop growth season in the arid region conforms to the form of a sine function:
wherein x is an image acquisition date DOY (DayofYear), and y is a daily evapotranspiration (mm/day); y is0、A、xcW is four unknown parameters in the sine function formula and is determined by fitting according to the calculated daily evapotranspiration numerical value of each pixel;
step S62: according to the sine function form, performing least square fitting by using the multi-temporal daily evapotranspiration of each pixel obtained in the step S5 to obtain y of each pixel0、A、xcW value, determining a specific equation in the step S61, integrating the growing seasons of different crops based on the spatial distribution of the crops in the step S3, and estimating the evapotranspiration spatial distribution condition of the growing seasons of the crops in the agricultural area
Compared with the prior art, the invention has the following beneficial effects:
the method combines the evapotranspiration change rule of the crop growth season, expands the daily evapotranspiration to the evapotranspiration of the crop growth season, and can provide effective reference for scientific management of farmland irrigation, accurate estimation of crop yield and optimal allocation of water resources.
Drawings
FIG. 1 is a flow chart of a method of an embodiment of the present invention;
FIG. 2 is a graph showing the instantaneous evapotranspiration and daily evapotranspiration profiles of crops at 137 and 256 days in an agricultural area, and the spatial evapotranspiration profile of a crop growing season, according to an embodiment of the present invention.
Detailed Description
The invention is further explained below with reference to the drawings and the embodiments.
Referring to fig. 1, the invention provides a high-resolution remote sensing estimation method for crop growth season evapotranspiration in an arid region, which comprises the following steps:
step S1: acquiring multi-temporal high-resolution remote sensing images (at least more than 4 scenes) of crop growth seasons in a research area, acquiring conventional meteorological observation data such as daily average temperature (DEG C), precipitation (mm), relative humidity (%) and wind speed (m/s), and collecting DEM data in the research area;
step S2: extracting crop planting information from the multi-temporal high-resolution remote sensing image to obtain crop distribution data of a research area;
step S3, constructing an SEBAL model according to crop distribution data in a research area, conventional meteorological observation data and DEM data in the research area;
step S4: calculating the instantaneous evapotranspiration of the remote sensing image acquisition time of the agricultural area based on the SEBAL model;
step S5: expanding the instantaneous evapotranspiration to daily evapotranspiration by a sine function method;
step S6: and performing time scale expansion estimation on the daily evapotranspiration based on the change rule of the crop growth season evapotranspiration to obtain the spatial distribution of the crop growth season evapotranspiration in the agricultural region.
In this embodiment, the step S4 specifically includes:
step S41: calculating the net surface radiant flux RnThe calculation formula is as follows:
Rn＝(1-α)Rs↓+RL↓-RL↑-(1-ε0)RL↓；
wherein α is the ground surface albedo, Rs↓ is solar short wave radiation incident to the earth surface, RL↓ is incident long wave radiation, RL×) is reflected long wave radiation; epsilon0Is the surface emissivity.
Step S42, calculating the soil heat flux G according to the following formula:
in the formula, TsIs the surface temperature, alpha is the surface albedo, NDVI is the normalized vegetation index, c11Is a satellite correction coefficient, and the transit time is 0.9 before 12 points at the local time and 1.0 between 12 points and 14 points.
Step S43, calculating the soil heat flux H according to the following formula:
in the formula, ρairIs the density of air, CpIs the specific heat of air at constant pressure, dT is the height Z from the ground1And Z2Temperature difference of (d) ofabIs the aerodynamic impedance.
Step S44, the earth surface radiation flux RnThe soil heat flux G and the sensible heat flux H are introduced into an energy balance equation to calculate the latent heat flux lambda ET at the satellite transit time, and the specific calculation formula is as follows:
Rn＝G+H+λET；
in the formula, RnIs the net radiant flux (J.m)-2·s-1) (ii) a G is the soil heat flux (J.m)-2·s-1) (ii) a H is sensible heat flux (J.m)-2·s-1) (ii) a λ ET is the latent heat flux (J · m) at the satellite transit time-2·s-1)。
Step S45: calculating instant evapotranspiration ET of satellite transit time by using latent heat flux lambda ET obtained by calculationinstThe specific calculation formula is as follows:
λ＝(2.501-0.002361×(TS-273.15))×106；
in the formula, ETinstIs an instantaneous evaporation method (J.m)-2·s-1) (ii) a Lambda is latent heat of vaporization (J.m)-2·s-1)。
In this embodiment, the step S5 specifically includes: estimating the daily evapotranspiration by the aid of a sine function according to the instantaneous evapotranspiration, wherein the specific calculation formula is as follows:
in the formula, NEThe number of evapotranspiration per day, t is the time interval from sunrise to satellite transit time,ETdailyfor daily evapotranspiration, ETinstIs an instant evapotranspiration.
In this embodiment, the step S6 specifically includes:
step S61: the evapotranspiration change rule of the crop growth season in the arid region conforms to the form of a sine function:
wherein x is an image acquisition date DOY (DayofYear), and y is a daily evapotranspiration (mm/day); y is0、A、xcW is four unknown parameters in the sine function formula and is determined by fitting according to the calculated daily evapotranspiration numerical value of each pixel;
step S62: according to the sine function form, performing least square fitting by using the multi-temporal daily evapotranspiration of each pixel obtained in the step S5 to obtain y of each pixel0、A、xcAnd w value, determining a specific equation in the step S61, integrating the growing seasons of different crops based on the spatial distribution of the crops in the step S3, and estimating the evapotranspiration spatial distribution condition of the growing seasons of the crops in the agricultural area.
In the present example, the agricultural region of open river basin in Xinjiang is used as the research region, remote sensing image data of 13 periods of the 2016 research region Landsat7(DOY:97, 113, 177, 209, 289, 305) and Landsat8(DOY:105, 137, 153, 217, 249, 265, 281) are used to estimate the evapotranspiration of the crop in the growing season, and FIG. 2 is the spatial distribution diagram of the instantaneous evapotranspiration and the daily evapotranspiration of the 137 th day and the 265 th day, respectively, and the evapotranspiration of the crop in the whole growing season.
The above description is only a preferred embodiment of the present invention, and all equivalent changes and modifications made in accordance with the claims of the present invention should be covered by the present invention.
Claims (5)
1. A high-resolution remote sensing estimation method for evapotranspiration of crops in arid regions is characterized by comprising the following steps:
step S1: acquiring multi-temporal high-resolution remote sensing images of crop growth seasons in a research area, acquiring conventional meteorological observation data, and collecting DEM data in the research area;
step S2: extracting crop planting information from the multi-temporal high-resolution remote sensing image to obtain crop distribution data of a research area;
step S3, constructing an SEBAL model according to crop distribution data in a research area, conventional meteorological observation data and DEM data in the research area;
step S4: calculating the instantaneous evapotranspiration of the remote sensing image acquisition time of the agricultural area based on the SEBAL model;
step S5: expanding the instantaneous evapotranspiration to daily evapotranspiration by a sine function method;
step S6: and performing time scale expansion estimation on the daily evapotranspiration based on the change rule of the crop growth season evapotranspiration to obtain the spatial distribution of the crop growth season evapotranspiration in the agricultural region.
2. The high-resolution remote sensing estimation method for the evapotranspiration of crops in the arid region according to claim 1, characterized by comprising the following steps of: the normal meteorological observation data include daily average air temperature (deg.C), precipitation (mm), relative humidity (%) and wind speed (m/s).
3. The method for estimating the high-resolution remote sensing of the evapotranspiration of the crops in the arid region according to claim 1, wherein the step S4 is specifically as follows:
step S41: calculating the net surface radiant flux RnThe calculation formula is as follows:
Rn＝(1-α)Rs↓+RL↓-RL↑-(1-ε0)RL↓；
wherein α is the ground surface albedo, Rs↓ is solar short wave radiation incident to the earth surface, RL↓ is incident long wave radiation, RL×) is reflected long wave radiation; epsilon0Is the surface emissivity.
Step S42, calculating the soil heat flux G according to the following formula:
in the formula, TsIs the surface temperature, alpha is the surface albedo, NDVI is the normalized vegetation index, c11Is a satellite correction coefficient, and the transit time is 0.9 before 12 points at the local time and 1.0 between 12 points and 14 points.
Step S43, calculating the soil heat flux H according to the following formula:
in the formula, ρairIs the density of air, CpIs the specific heat of air at constant pressure, dT is the height Z from the ground1And Z2Temperature difference of (d) ofabIs the aerodynamic impedance.
Step S44, the earth surface radiation flux RnThe soil heat flux G and the sensible heat flux H are introduced into an energy balance equation to calculate the latent heat flux lambda ET at the satellite transit time, and the specific calculation formula is as follows:
Rn＝G+H+λET；
in the formula, RnIs the net radiant flux (J.m)-2·s-1) (ii) a G is the soil heat flux (J.m)-2·s-1) (ii) a H is sensible heat flux (J.m)-2·s-1) (ii) a λ ET is the latent heat flux (J · m) at the satellite transit time-2·s-1)。
Step S45: calculating instant evapotranspiration ET of satellite transit time by using latent heat flux lambda ET obtained by calculationinstThe specific calculation formula is as follows:
λ＝(2.501-0.002361×(TS-273.15))×106；
in the formula, ETinstIs an instantaneous evaporation method (J.m)-2·s-1) (ii) a Lambda is latent heat of vaporization (J.m)-2·s-1)。
4. The method for estimating the high-resolution remote sensing of the evapotranspiration of the crops in the arid region according to claim 3, wherein the step S5 is specifically as follows: estimating the daily evapotranspiration by the aid of a sine function according to the instantaneous evapotranspiration, wherein the specific calculation formula is as follows:
in the formula, NEThe number of evapotranspiration per day, t is the time interval from sunrise to satellite transit time, ETdailyFor daily evapotranspiration, ETinstIs an instant evapotranspiration.
5. The method for estimating the high-resolution remote sensing of the evapotranspiration of the crops in the arid region according to claim 4, wherein the step S6 is specifically as follows:
step S61: the evapotranspiration change rule of the crop growth season in the arid region conforms to the form of a sine function:
wherein x is an image acquisition date DOY (day of Yeast), and y is a daily evapotranspiration (mm/day); y is0、A、xcW is four unknown parameters in the sine function formula and is determined by fitting according to the calculated daily evapotranspiration numerical value of each pixel;
step S62: according to the sine function form, performing least square fitting by using the multi-temporal daily evapotranspiration of each pixel obtained in the step S5 to obtain y of each pixel0、A、xcAnd w value, determining a specific equation in the step S61, integrating the growing seasons of different crops based on the spatial distribution of the crops in the step S3, and estimating the evapotranspiration spatial distribution condition of the growing seasons of the crops in the agricultural area.
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| CN114663778A (en) * | 2022-03-17 | 2022-06-24 | 中国农业大学 | Method and device for improving crop yield |
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| CN114663778A (en) * | 2022-03-17 | 2022-06-24 | 中国农业大学 | Method and device for improving crop yield |
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Application publication date: 20191220 |
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| RJ01 | Rejection of invention patent application after publication |