A method for determining water use efficiency of vegetation layer and ET-GPP-WUE measuring device

Abstract

The invention discloses a method for determining the water use efficiency of the vegetation layer and an ET-GPP-WUE measuring device, which belongs to the field of water resource protection in agriculture and forestry. The method includes: WUE is the ratio of GPP to ET, the method includes: GPP is calculated by the TG model, ET is calculated by the improved MEP, and the input parameters are surface specific humidity, surface temperature, vegetation leaf area, surface net radiation, vegetation net radiation, air specific humidity and air temperature. The input parameters of the improved MEP model, surface specific humidity, vegetation leaf area, surface net radiation, vegetation net radiation, air specific humidity and air temperature, are obtained by real-time field collection of the measured area, and the input parameter leaf area index of the TG model is obtained by real-time calculation based on the vegetation leaf area collected in the field; the input parameter surface temperature of the improved MEP model and the input parameter land surface temperature of the TG model are obtained by real-time field collection of the measured area by the same temperature sensor. The invention couples ET and GPP through surface temperature and leaf area to avoid inconsistency between internal independent ET and GPP models.

Description

Technical Field

[0001] The invention belongs to the field of water resource protection in agriculture and forestry, and more specifically, relates to a method for determining water use efficiency of a vegetation layer and an ET-GPP-WUE measuring device. Background Art

[0002] Evapotranspiration (ET) is the second largest water flux in the terrestrial water cycle, accounting for about 60%-70% of precipitation. In the methods for calculating ET, the traditional acquisition of actual evapotranspiration is mainly based on ground observation data. Most models are based on water vapor transport and energy balance constraints and are calculated using ground meteorological stations. The results are all reference crop evaporation, while the acquisition of actual evapotranspiration is still insufficient. The method for determining the gross primary productivity (GPP) of terrestrial ecosystems can currently only be estimated through lower-resolution satellite remote sensing data and models (VPM model, EC-LUE, temperature and greenness GT model, etc.), which reduces the accuracy of the results. This will lead to increased uncertainty in runoff areas, watersheds and local scales, making it difficult to meet practical application needs.

[0003] One of the definitions of ecosystem WUE (Water User Efficiency) is gross primary productivity (GPP) / evapotranspiration (ET). In 2005, Rahman et al. proposed a method to estimate the gross primary production of deciduous and evergreen forests based on the total primary production observed by the eddy flux tower, introduced vegetation index and ground temperature, established a temperature and greenness model (TG model), and estimated the gross primary production of deciduous and evergreen forests. Its input parameters were leaf area index (greenness value), land surface temperature, and unit conversion coefficient m. In 2011, Wang JF et al. established a method to estimate the surface latent heat (evapotranspiration) based on the maximum entropy increase theory (Maximum Entropy Production, MEP) to calculate ET. Its input parameters were net radiation, surface temperature, and surface specific humidity.

[0004] In the prior art, in the WUE calculation process, among the three input variables of the TG model, the scalar m is usually calculated from the annual average nighttime land surface temperature, and the land surface temperature and leaf area index are calculated based on remote sensing products; among the three input variables of the MEP model, the net radiation and surface temperature variables are usually directly provided by the eddy covariance data set FLUXNET2015, while the specific humidity is calculated based on the Clausius-clapeyron equation. The different data sources of the TG model and the MEP model lead to internal inconsistency in the data during the WUE calculation process, which in turn affects the calculation accuracy of WUE. In addition, most of the existing methods are based on remote sensing data, resulting in low resolution and difficulty in obtaining data. If affected by weather, the reliability is questionable; the GPP products obtained based on historical data are difficult to make reasonable predictions about the current situation, affecting the timeliness of the analysis results. Summary of the invention

[0005] In view of the defects of the prior art and the need for improvement, the present invention provides a method for determining the water use efficiency of the vegetation layer and an ET-GPP-WUE measuring device, the purpose of which is to calculate WUE by coupling ET and GPP of surface temperature T and leaf area, with fewer variables required (only temperature, specific humidity, leaf area, etc.), high spatial resolution, and more suitable for field / forest scale, large regional scale, etc.

[0006] To achieve the above object, according to a first aspect of the present invention, a method for determining water use efficiency of a vegetation layer is provided, wherein the water use efficiency WUE is the ratio of the gross primary productivity GPP to the evapotranspiration ET.

[0007] The method comprises: the GPP is calculated by using a temperature and greenness model, and the ET is calculated by using an improved maximum entropy increase model, wherein the input parameters are surface specific humidity, surface temperature, vegetation leaf area, surface net radiation, vegetation net radiation, air specific humidity and air temperature, and the calculation formula of evapotranspiration ET in the improved maximum entropy increase model is as follows:

[0008]

[0009] Among them, E s represents soil evaporation, E v Indicates vegetation emanation, S v represents the leaf area of ​​vegetation in the measured area, and B represents the area of ​​the measured area;

[0010] The input parameters of the improved maximum entropy increase model, namely, surface specific humidity, vegetation leaf area, surface net radiation, vegetation net radiation, air specific humidity and air temperature, are obtained by real-time field collection of the vegetation layer in the measured area. The input parameter leaf area index of the temperature and greenness model is obtained by real-time calculation based on the vegetation leaf area collected in the field. The input parameters of the improved maximum entropy increase model, namely, surface temperature and land surface temperature, are obtained by real-time field collection of the measured area by the same temperature sensor.

[0011] Preferably, the vegetation emits E v The calculation formula is as follows:

[0012]

[0013]

[0014]

[0015] Among them, R n1 represents the net radiation of vegetation, B(·) is the inverse of the Bowen ratio, σ 1is a dimensionless function of air temperature and surface water vapor density, λ represents the latent heat of water phase change, R v represents the water vapor constant, c p represents the specific heat of air at normal pressure, q s1 Indicates the specific humidity of air, T s1 Indicates the air temperature.

[0016] To achieve the above object, according to a second aspect of the present invention, there is provided an ET-GPP-WUE measurement device applicable to different vegetation layers, the device comprising: a fixing mechanism, an adjustment mechanism, a measurement mechanism, an integrated control center and a power supply;

[0017] The fixing mechanism is a telescopic rod with adjustable height. During the measurement process, one end of the rod is inserted into the measured area to fix the entire measuring device. The height of the rod is adjusted according to the height of the vegetation layer in the measured area, and the other end is connected to the adjusting mechanism.

[0018] The adjusting mechanism comprises a support and a bearing, the support is connected to the fixing mechanism, and the bearing is connected to the measuring mechanism, and is used to adjust the measuring angle of the measuring mechanism;

[0019] The measuring mechanism includes: surface specific humidity collector, surface temperature collector, vegetation leaf area collector, surface net radiation collector, vegetation net radiation collector, air specific humidity collector and air temperature collector, which respectively communicate with the integrated control center in real time via Bluetooth;

[0020] The integrated control center determines ET, GPP and WUE using the method described in the first aspect;

[0021] The power supply is connected to the measuring mechanism and the integrated control center to supply power to them during the measuring process.

[0022] Preferably, the surface humidity collector, surface temperature collector, and surface net radiation collector are integrated at the same location, and the vegetation net radiation collector, air humidity collector, and air temperature collector are integrated at the same location. The integrated collector for collecting surface humidity is close to the surface, and the integrated collector for collecting vegetation / air is close to and above the vegetation layer, and is generally set up 1 to 2 meters above the vegetation layer.

[0023] Preferably, the integrated control center transmits the measurement results ET, GPP and WUE to a data storage or database via wired or wireless means.

[0024] Preferably, the vegetation leaf area collector comprises: a laser scanner and a vegetation leaf area calculation module;

[0025] The laser scanner is used to emit two parallel laser beams, which are incident on the surface of leaves in the forest / field to collect leaf images;

[0026] The vegetation leaf area calculation module is used to calculate the vegetation leaf area based on the leaf image. The calculation formula is as follows:

[0027] S v =(a*d*d) / (s*s)

[0028] Among them, a represents the pixel of the leaf on the image, d represents the distance between the two laser points, and s represents the pixel spacing between the light points on the image.

[0029] Preferably, the vegetation layer temperature collector, the air specific humidity collector, and the vegetation layer net radiation collector respectively use infrared temperature sensors, Finna Sensors near-infrared humidity sensors, and net radiation meters.

[0030] Preferably, the device also includes a display module for intuitively displaying net radiation, specific humidity, vegetation leaf area, leaf area index, surface temperature, and measurement results ET, GPP, and WUE. In general, the above technical solutions conceived by the present invention can achieve the following beneficial effects:

[0031] (1) The present invention uses a temperature and greenness model to calculate GPP and an improved maximum entropy increase model to calculate ET. The input parameters of the improved maximum entropy increase model, namely, surface specific humidity, vegetation leaf area, surface net radiation, vegetation net radiation, air specific humidity and air temperature, are obtained by real-time field collection of the vegetation layer in the measured area. The input parameter leaf area index of the temperature and greenness model is obtained by real-time calculation based on the vegetation leaf area collected in the field. The input parameter surface temperature of the improved maximum entropy increase model and the input parameter land surface temperature of the temperature and greenness model are obtained by real-time field collection of the measured area by the same temperature sensor. Temperature and leaf area changes are continuous states, and it is difficult to achieve continuous monitoring with remote sensing data. The present invention couples ET and GPP with surface temperature T and leaf area, and uses real-time field measured data to avoid inconsistencies between internal independent ET and GPP models. It has the advantages of high simulation accuracy, few required variables, easy implementation, more reliability, less weather influence, and easy acquisition.

[0032] (2) The present invention improves the MEP model, taking into account the effects of temperature and solar radiation on it, as well as the influence of vegetation coverage on the estimation of ET. The improved MEP model only requires leaf area index, surface temperature, specific humidity, and net radiation to calculate the continuous change trend of ET.

[0033] (3) The present invention forms a data warehouse by transmitting data to the terminal in a wireless manner, and can perform in-depth analysis through OLAP technology of data mining, which is more conducive to in-depth evaluation of the coupling effect of ET and GPP. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] Figure 1 A flow chart of a method for determining water utilization efficiency of vegetation layer provided by the present invention;

[0035] Figure 2 This is a schematic diagram of the structure of an ET-GPP-WUE measurement device suitable for different vegetation layers provided by the present invention. DETAILED DESCRIPTION

[0036] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention. In addition, the technical features involved in each embodiment of the present invention described below can be combined with each other as long as they do not conflict with each other.

[0037] like Figure 1 As shown, the present invention provides a method for determining the water use efficiency of the vegetation layer, where the water use efficiency WUE is the ratio of the gross primary productivity GPP to the evapotranspiration ET.

[0038] The method comprises: the GPP is calculated by using a temperature and greenness model, and the ET is calculated by using an improved maximum entropy increase model, wherein the input parameters are surface specific humidity, surface temperature, vegetation leaf area, surface net radiation, vegetation net radiation, air specific humidity and air temperature, and the calculation formula of evapotranspiration ET in the improved maximum entropy increase model is as follows:

[0039]

[0040] Among them, E s represents soil evaporation, E v Indicates vegetation emanation, S v represents the leaf area of ​​vegetation in the measured area, and B represents the area of ​​the measured area;

[0041] The input parameters of the improved maximum entropy increase model, namely, surface specific humidity, vegetation leaf area, surface net radiation, vegetation net radiation, air specific humidity and air temperature, are obtained by real-time field collection of the vegetation layer in the measured area. The input parameter leaf area index of the temperature and greenness model is obtained by real-time calculation based on the vegetation leaf area collected in the field. The input parameters of the improved maximum entropy increase model, namely, surface temperature and land surface temperature, are obtained by real-time field collection of the measured area by the same temperature sensor.

[0042] Preferably, the vegetation emits E v The calculation formula is as follows:

[0043]

[0044]

[0045]

[0046] Among them, R n1 represents the net radiation of vegetation, B(·) is the inverse of the Bowen ratio, σ 1 is a dimensionless function of air temperature and surface water vapor density, λ represents the latent heat of water phase change, R v represents the water vapor constant, c p represents the specific heat of air at normal pressure, q s1 Indicates the specific humidity of air, T s1 Indicates the air temperature.

[0047] like Figure 2 As shown, the present invention provides an ET-GPP-WUE measuring device suitable for different vegetation layers, which mainly includes: an infrared temperature sensor, a Finna Sensors near-infrared (NIR) humidity sensor, a net radiometer, an image acquisition and processing system, an integrated control center, a database storage system, a data transmission interface, a video monitoring system, a display, a laser tube, a housing, and a bracket.

[0048] The image acquisition and processing system uses advanced information technologies such as the Internet of Things, cloud computing, big data, and the Internet to uniformly analyze and process vegetation layer information such as temperature, humidity, net radiation, and leaf area index in the detection area, and presents the results of the system analysis to managers in an intuitive and vivid way. Managers can grasp information such as GPP, ET, and WUE through real-time video and data processing results. It plays an auxiliary role in improving the ability to manage water and carbon resources.

[0049] Among them, the infrared temperature sensor can extract multi-point surface temperature information from the vegetation layer information; the FinnaSensors near-infrared (NIR) humidity sensor is used to extract multi-point surface specific humidity from the vegetation layer information.

[0050] The laser tube is fixed on the bracket and emits two parallel laser beams, which are incident on the surface of leaves in the forest / field. The camera collects images, and the image processing system analyzes the collected status information and process quantity information to obtain characteristic parameters and thresholds.

[0051] Assume that the distance between the two laser points is d, the pixel spacing between the light points on the image is s, and the pixel of the leaf on the image is a, then the leaf area S v Calculation formula:

[0052] S v =(a×d×d) / (s×s)

[0053] Among them, the pixel a is obtained by program counting, and the spacing s is obtained by the image processing program, using the grayscale centroid formula:

[0054]

[0055]

[0056] Among them, i 0 is the first coordinate of the i-th row, i f is the last coordinate of the i-th row, j 0 is the first coordinate of the jth column, j f is the last coordinate of the jth column, T is the grayscale threshold of the light spot image, f is the grayscale value of each pixel, x and y are the grayscale center coordinates of the light spot. The difference between the grayscale center coordinates of the two laser spots formed by the two beams of light emitted by the laser is the spacing s.

[0057] The accuracy of the grayscale centroid algorithm is 0.02 pixels. In the image processing system, each pixel corresponds to 0.1 mm. The light spot calibration accuracy of this device is 0.002 mm.

[0058] LAI (leaf area index) or greenness value according to the formula: LAI = S v / B can be calculated. Where B is the area of ​​the entire area occupied by the relative plant leaf area in the scanner. S v The corresponding area of ​​the raster image occupied by the plant leaf area in the image presented by the scanner, that is, the area occupied by the non-white part of the entire layer, is calculated by the image processing system.

[0059] The method of using the integrated acquisition device for plant leaf emanation, total primary productivity, and water use efficiency is as follows: obtain the temperature, humidity, leaf area and other information of the field vegetation layer through non-contact multi-sensors (infrared temperature sensor, Finna Sensors near-infrared (NIR) humidity sensor, laser scanner), calculate the vegetation layer LAI (leaf area index or greenness value) according to the characteristics of the erection platform and the vegetation type; extract multi-point surface temperature information from the vegetation layer information, and calculate the total primary productivity based on the temperature and greenness model. The required net radiation is collected and processed by a net radiometer; extract multi-point surface specific humidity from the vegetation layer information, calculate the actual evapotranspiration based on the maximum entropy increase model, and calculate the water use efficiency according to GPP / ET. The analysis and storage of the data of the present invention can be transmitted wirelessly to the data storage device or database of the configured laptop terminal.

[0060] The maximum entropy evapotranspiration (MEP) model is a new surface evapotranspiration theoretical framework established on the basis of comprehensive reference to Bayesian probability theory, information entropy concept, non-equilibrium thermodynamics theory and atmospheric boundary layer turbulence similarity theory, which overcomes the main defects of the classical model. The calculation formula of the MEP-ET model is:

[0061] Es=B(σ)H

[0062]

[0063] Es+H+Q=R n

[0064]

[0065] Among them, H is the (turbulent) sensible heat flux entering the atmosphere, Q is the conductive heat flux entering the surface medium (soil or vegetation); Rn is the net radiation of the surface; B is the inverse of the Bowen ratio; σ is a dimensionless function of surface temperature and surface water vapor density, which is an important parameter in the model. It quantitatively describes the relative importance of surface moisture temperature conditions to the evapotranspiration process, especially the dominant role of water phase change in surface energy balance and ground-air water heat exchange. See the following formula for details:

[0066]

[0067] Among them, q s is the specific humidity of air on the evaporating surface; Ts (K) is the surface temperature of the evaporating body; λ is the latent heat of phase change of water (J / kg); cp is the specific heat of air (constant pressure); R v is the gas constant of water vapor [461 J / (kg·K)]; ɑ is the ratio of the turbulent diffusivity of water vapor to the thermal diffusivity in the boundary layer. Theoretically, the two diffusivities can be different, and it is generally assumed that ɑ=1.

[0068]

[0069]

[0070] LAI is the measured value, E s is soil evaporation, E v is the vegetation radiance, E is the evapotranspiration rate (latent heat flux), S v is the vegetation area, and B is the area of ​​the entire region occupied by the relative plant leaf area in the scanner.

[0071] The calculation of GPP adopts the TG (temperature and greenness model). The TG model is a GPP estimation model based on remote sensing. It does not require ground observation data as model input and is a GPP model based entirely on remote sensing data.

[0072] GPP = m × (LAI scaled ×LST scaled )

[0073] LAI scaled =LAI-0.1

[0074] LST scaled=min[(LST / 30);(2.5-(0.05LST))]

[0075] Among them, the parameter m is obtained through model calibration; LST (Land surface temperature) is the land surface temperature.

[0076] The integrated control center is the core module of the present invention. On the one hand, it receives data information from various sensors and performs signal processing, feature extraction, threshold calculation and other operations on the sensor data; on the other hand, it sends vegetation layer information and raw data in the online monitoring process to the terminal through data analysis results.

[0077] The measurement results are displayed on the laptop terminal and transmitted to the database storage system in a wired or wireless manner through the data transmission interface. The serial USB module can be connected to record on a U disk file, the serial SD module can be connected to record on an SD card file, the serial wireless module can be connected to the server database wirelessly, and can also be connected to the Internet through the DSP network interface. Bluetooth transmission, wireless network transmission, etc. can also be realized. The data transmission interface is mainly used for data communication between the integrated control center and the video surveillance center.

[0078] The vegetation layer information of forests and fields is obtained through non-contact multi-sensors. The laser is incident on the leaf surface of forests and fields through the erected platform. Then, the acquired characteristic parameters and thresholds are processed by the image acquisition and processing system and transmitted to the integrated control center to calculate the leaf area index (or greenness value) of the preparation layer. The infrared temperature sensor and Finna Sensors near-infrared (NIR) humidity sensor transmit the acquired surface temperature information and specific humidity to the integrated control center to calculate the actual T value based on the maximum entropy increase model (MEP). In the integrated control center, the leaf area index (or greenness) and multi-point surface temperature information are coupled to calculate the GPP based on the temperature and greenness model, and finally the water use efficiency is obtained according to GPP / T.

[0079] The method and device that couples T and GPP together for simultaneous acquisition and rapid calculation have high temporal and spatial resolution and a certain degree of spatial integration (i.e., the entire forest canopy is considered as a whole, rather than focusing on a single plant). In addition, "near-ground" remote sensing is more targeted than satellite remote sensing, and high-definition digital images can also be used as ground verification information. Moreover, digital images are much easier to process than satellite images. This will have a broad and far-reaching impact on the estimation and application of GPP in the future.

[0080] It will be easily understood by those skilled in the art that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for determining the water use efficiency of vegetation layer, wherein the water use efficiency WUE is the ratio of the gross primary productivity GPP to the evapotranspiration ET, characterized in that: The method comprises: the GPP is calculated by using a temperature and greenness model, and the ET is calculated by using an improved maximum entropy increase model, wherein the input parameters are surface specific humidity, surface temperature, vegetation leaf area, surface net radiation, vegetation net radiation, air specific humidity and air temperature, and the calculation formula of evapotranspiration ET in the improved maximum entropy increase model is as follows: Among them, E s represents soil evaporation, E v Indicates vegetation emanation, S v represents the leaf area of ​​vegetation in the measured area, and B represents the area of ​​the measured area; The input parameters of the improved maximum entropy increase model, namely, surface specific humidity, vegetation leaf area, surface net radiation, vegetation net radiation, air specific humidity and air temperature, are obtained by real-time field collection of the vegetation layer in the measured area. The input parameter leaf area index of the temperature and greenness model is obtained by real-time calculation based on the vegetation leaf area collected in the field. The input parameters of the improved maximum entropy increase model, namely, surface temperature and land surface temperature, are obtained by real-time field collection of the measured area by the same temperature sensor.

2. The method according to claim 1, characterized in that Vegetation E v The calculation formula is as follows: Among them, R n1 represents the net radiation of vegetation, B(·) is the inverse of the Bowen ratio, σ1 is a dimensionless function of air temperature and surface water vapor density, λ represents the latent heat of phase change of water, R v represents the water vapor constant, c p represents the specific heat of air at normal pressure, q s1 Indicates the specific humidity of air, T s1 Indicates the air temperature.

3. An ET-GPP-WUE measurement device suitable for different vegetation layers, characterized in that: The device comprises: a fixing mechanism, an adjusting mechanism, a measuring mechanism, an integrated control center and a power supply; The fixing mechanism is a telescopic rod with adjustable height. During the measurement process, one end of the rod is inserted into the measured area to fix the entire measuring device. The height of the rod is adjusted according to the height of the vegetation layer in the measured area, and the other end is connected to the adjusting mechanism. The adjusting mechanism comprises a support and a bearing, the support is connected to the fixing mechanism, and the bearing is connected to the measuring mechanism, and is used to adjust the measuring angle of the measuring mechanism; The measuring mechanism includes: surface specific humidity collector, surface temperature collector, vegetation leaf area collector, surface net radiation collector, vegetation net radiation collector, air specific humidity collector and air temperature collector, which respectively communicate with the integrated control center in real time via Bluetooth; The integrated control center determines ET, GPP and WUE using the method as claimed in claim 1 or 2; The power supply is connected to the measuring mechanism and the integrated control center to supply power to them during the measuring process.

4. The device according to claim 3, characterized in that The surface specific humidity collector, the surface temperature collector and the surface net radiation collector are integrated at the same position; the vegetation net radiation collector, the air specific humidity collector and the air temperature collector are integrated at the same position.

5. The device according to claim 3 or 4, characterized in that The integrated control center transmits the measurement results ET, GPP and WUE to a data storage device or a database via wired or wireless means.

6. The device according to claim 3, characterized in that The vegetation leaf area collector comprises: a laser scanner and a vegetation leaf area calculation module; The laser scanner is used to emit two parallel laser beams, which are incident on the surface of leaves in the forest / field to collect leaf images; The vegetation leaf area calculation module is used to calculate the vegetation leaf area based on the leaf image. The calculation formula is as follows: S v =(a*d*d) / (s*s) Among them, a represents the pixel of the leaf on the image, d represents the distance between the two laser points, and s represents the pixel spacing between the light points on the image.

7. The device according to claim 3, characterized in that The vegetation layer temperature collector, air specific humidity collector, and vegetation layer net radiation collector use infrared temperature sensors, Finna Sensors near-infrared humidity sensors, and net radiation meters, respectively.

8. The device according to claim 3, characterized in that The device also includes a display module for intuitively displaying net radiation, specific humidity, vegetation leaf area, leaf area index, surface temperature, and measurement results ET, GPP, and WUE.

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