CN117350082A - Calculation method for net ecological system productivity - Google Patents
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Abstract
The invention discloses a calculation method of net ecological system productivity, and belongs to the technical field of climate change. Comprising the following steps: s1: constructing a TL-LUE-NEP model according to a NEP=GPP-Re relation; s2: selecting and correcting key parameters in TL-LUE-NEP modelThe method comprises the steps of carrying out a first treatment on the surface of the S3: collecting and processing required data; s4: correcting and verifying parameters on siteAccuracy of (2); s5: and comprehensively evaluating the effect of the model and the correction on the site scale. The invention constructs the calculation method of the net ecological system productivity based on the TL-LUE-NEP model based on the TL-LUE and TP models which are widely used, the method has higher precision for estimating the net ecological system productivity, the method is simple and easy to operate, the parameters are fewer, the data are easy to obtain, and the method is a quantization areaDomain carbon absorption provides an efficient method to provide reliable reference data for regional carbon balance and measuring its carbon source/sink effect.
Description
Technical Field
The invention belongs to the technical field of climate change, and particularly relates to a calculation method of net ecological system productivity.
Background
Net Ecosystem Productivity (NEP) is the residual carbon content of plant photosynthesis (GPP, total primary productivity of the ecosystem) minus the ecosystem respiration (Re), describing the carbon absorption capacity of the terrestrial ecosystem in terms of mass and quantity, helping to quantify the carbon absorption of the terrestrial ecosystem. The net ecological system productivity not only can reflect the influence of climate change and human social and economic activities on land vegetation to a certain extent, but also can determine the carbon balance of the land ecological system and measure the important indexes of carbon sources or carbon sinks thereof. When net ecosystem productivity is positive, this indicates that the ground is carbon sink; when it is negative, it means that the ground is a carbon source. Therefore, the net ecosystem productivity provides a data reference for controlling and reducing greenhouse gas emissions, achieving dual carbon targets early and promoting green low carbon development.
The models simulating the productivity of the net ecological system mainly comprise a statistical model, a process model and a remote sensing model. The statistical model is an empirical model established according to the correlation of the measured net ecological productivity and the climate factors. The process model considers plant growth and development processes according to physiological characteristics, weather and environmental conditions of different types of vegetation, and has practical significance, such as a BEPS model, an InTEC model and the like. The remote sensing model is mostly built according to the light energy utilization rate and plant photosynthesis, and the light energy utilization rate model mainly comprises a CASA model, an SDBM model and the like.
At present, the statistical model often lacks credible theoretical support and actual physiological significance, and meanwhile, differences of growth environments of different areas are ignored to a certain extent, so that the reliability of a simulation result is affected. Many parameters are required in the process model as input data, increasing the uncertainty in the net ecosystem productivity estimate. While Light Utilization Efficiency (LUE) models can well estimate GPP for various spatial and temporal scales, they can utilize a wide range of telemetry data. Most LUE models, such as CASA model, MOD17 model, VPM model, treat the vegetation canopy as large leaves, ignoring differences in solar radiation absorption and LUE within the canopy. The vegetation canopy is divided into a male leaf and a female leaf in the vegetation canopy by a two-leaf light energy utilization rate model (TL-LUE) model, vegetation productivity is calculated respectively, and simulation accuracy under the scattered radiation condition is improved. Therefore, the advantages of using the TL-LUE model for GPP estimation and the TP model for Re estimation are utilized to build the TL-LUE-NEP model for estimating regional net ecosystem productivity. The model has potential in researching the carbon absorption of an ecological system, and the application is not wide enough at present.
Disclosure of Invention
The invention solves the technical problems that: in order to accurately estimate the net ecosystem productivity and thus the carbon absorption, a calculation method of the net ecosystem productivity is proposed.
The technical scheme is as follows: in order to solve the technical problems, the invention adopts the following technical scheme:
a method of calculating net ecosystem productivity, comprising the steps of:
s1: constructing a TL-LUE-NEP model according to a NEP=GPP-Re relation;
s2: selecting and correcting key parameters in TL-LUE-NEP model；
S3: collecting and processing required data;
s4: correcting and verifying parameters on siteAccuracy of (2);
s5: and comprehensively evaluating the effect of the model and the correction on the site scale.
Preferably, in step S1, a TL-LUE model and a TP model are selected to construct a TL-LUE-NEP model, the TL-LUE model and the TP model respectively generate total primary productivity and ecosystem respiration, and NEP is obtained according to a relationship of nep=gpp-Re;
where GPP is total primary productivity, re is ecosystem respiration, NEP is net ecosystem productivity.
Preferably, in step S2, in order to facilitate the subsequent region simulation, the LAI product is used as input data, and parameters related to LAI in the model need to be correctedParameter correction is according to the formula:
where m is the number of all measured values,andestimated and measured net ecosystem productivity, respectively;is the average of the net ecosystem productivity measured; according to this formula, the sites involved in correction are all optimized。
Preferably, in step S3, daily weather data and sites with complete actual measured net ecosystem productivity data in the FLUXNET2015 site are collected, whether the data are defective is checked, if data of more than two months in one year are missing, the data of the site in the year are deleted, missing data of less than two months in one year are interpolated, and finally the required data of the site are ensured to be complete.
Preferably, in step S3, the LAI of the site is extracted from the LAI product according to the longitude and latitude of the required site, and the maximum LAI of the site in one year is considered as LAImax data, and the LAI data is used as input data to participate in correction.
Preferably, in step S4, all sites are classified according to vegetation types, 3/4 sites are randomly calculated in each vegetation type for correction, and 1/4 sites are used for verification; finally, 79 sites were used for parameter correction and 24 sites were used for parameter verification.
Preferably, in step S4, 79 site pairs are utilized for parametersCorrection is carried out, the parameter correction range is set to be 0.001-4, and each site obtains an optimal valueValues.
Preferably, in step S4, the parameters are verified: will correct the site's bestAnd (5) sorting and averaging according to vegetation types, and then carrying the parameter average value of each vegetation type into a model for simulation.
Preferably, in step S5, use is made ofAnd RMSE assessment of the accuracy of modeling net ecosystem productivity,and the calculation formulas of RMSE are respectively:
where n is the number of measurement data,、/>estimating and measuring net ecosystem productivity data respectively; />Is an average value of estimated net ecosystem productivity data,/->Is the average value of the actual measurement net ecological system productivity data; and calculating the slope and intercept between the simulated net ecological system productivity and the actual ecological system productivity by using linear regression, and further evaluating the performance of the simulated net ecological system productivity.
Preferably, in step S5, simulated net ecosystem productivity data of eight days, months or years may also be accumulated, and compared with actual net ecosystem productivity at the corresponding scale, the performance of the model at different scales may be observed.
The beneficial effects are that: compared with the prior art, the invention has the following advantages:
(1) The method constructs a calculation method of the net ecological system productivity based on the TL-LUE-NEP model based on widely used TL-LUE and TP models, and the site verification shows that the method has higher accuracy in estimating the net ecological system productivity; the whole method is simple and easy to operate, has fewer parameters and easy to acquire data, provides an effective method for quantifying regional carbon absorption, and provides reliable reference data for regional carbon balance and measuring carbon source/sink effects.
Drawings
FIG. 1 is a flow chart of a method of calculating net ecosystem productivity;
FIG. 2 is a graph of simulated GPP (simulated total primary yield of ecosystem) and measured GPP of various vegetation types at calibration of the present invention EC A scatter plot of (measured total primary productivity of ecosystem) comparison;
FIG. 3 is a simulated Re (simulated ecosystem respiration) and measured Re for each vegetation type at the time of correction of the present invention EC A scatter plot of (measured ecosystem respiration) contrast;
FIG. 4 is a simulated NEP (simulated net ecosystem productivity) and measured NEP for each vegetation type at calibration of the present invention EC (actual measurement of the Net)Ecosystem productivity) versus scatter plot;
FIG. 5 is a simulated GPP (simulated total primary yield of ecosystem) and measured GPP of vegetation types at the time of the test of the present invention EC A scatter plot of (measured total primary productivity of ecosystem) comparison;
FIG. 6 is a simulated Re (simulated ecosystem respiration) and measured Re for each vegetation type at the time of the test of the present invention EC A scatter plot of (measured ecosystem respiration) contrast;
FIG. 7 is a simulated NEP (simulated net ecosystem productivity) and measured NEP for each vegetation type at the time of the test of the present invention EC (measured net ecosystem productivity) versus scatter plot.
Detailed Description
The invention will be further illustrated with reference to specific examples, which are carried out on the basis of the technical solutions of the invention, it being understood that these examples are only intended to illustrate the invention and are not intended to limit the scope thereof.
As shown in fig. 1-7, the present invention proposes a method for calculating net ecosystem productivity.
In the embodiment of the invention, when the key parameters of the TL-LUE-NEP model are corrected, the FLUXNET2015 sites used are distributed worldwide and comprise nine regional types. The corrected model can be used for global net ecosystem productivity calculations. The specific steps of the invention are as follows:
s1: constructing TL-LUE-NEP model according to NEP=GPP-Re relation
And selecting a TL-LUE model and a TP model to construct a TL-LUE-NEP model, respectively generating total primary productivity (GPP) and ecosystem respiration (Re) by the TL-LUE model and the TP model, and obtaining NEP (net ecosystem productivity) according to the relationship of NEP=GPP-Re.
S2: selecting and correcting key parameters in TL-LUE-NEP model
To facilitate region simulation, error reduction is achieved using LAI productsAs input data, it is therefore necessary to correct the LAI-related parameters in the modelParameter correction is according to the formula:
where m is the number of all measured values,andestimated and measured net ecosystem productivity, respectively.Is the average of the net ecosystem productivity measured. According to this formula, the sites involved in correction are all optimized。
S3: collecting and processing required data
(1) Downloading daily-scale meteorological data and a site with complete actual measurement net ecological system productivity data in a FLUXNET2015 site, checking whether the data are defective, deleting the data of the site in the year if the data of more than two months in the year are missing, interpolating missing data of less than two months in the year, and finally ensuring that the required data of the site are complete; a total of 103 sites were eventually available, belonging to 9 different vegetation types.
(2) And extracting the LAI of the station from the LAI product according to the longitude and latitude of the required station, and considering the maximum value of the LAI of the station as LAImax data in one year, and taking the LAI as input data to participate in correction.
S4: correcting and verifying parameters on siteAccuracy of (a)
(1) Classifying all sites according to vegetation types, randomly calculating 3/4 sites in each vegetation type for correction, and 1/4 sites for verification; finally, 79 sites were used for parameter correction and 24 sites were used for parameter verification.
(2) Parameters using 79 site pairsCorrection is carried out, the parameter correction range is set to be 0.001-4, and each site obtains an optimal valueValues.
(3) Then, verification is performed to correct the best of the siteAnd (5) sorting and averaging according to vegetation types, and then carrying the parameter average value of each vegetation type into a model for simulation.
S5: comprehensive assessment model and correction effect on site scale
Using(determining coefficients) and RMSE (root mean square error) to assess the accuracy of modeling net ecosystem productivity,and the calculation formulas of RMSE are respectively:
where n is the number of measurement data,、/>is an estimated and measured net ecosystemSystem productivity data. />Is an average value of estimated net ecosystem productivity data,/->Is the average value of the actual measurement net ecological system productivity data; and calculating the slope and intercept between the simulated net ecological system productivity and the actual ecological system productivity by using linear regression, and further evaluating the performance of the simulated net ecological system productivity.
As shown in fig. 2-7, the performance of the simulated net ecosystem productivity of the site is corrected and verified at the daily scale including ENF (Evergreen Needleleaf Forest, evergreen conifer), DBF (Deciduous Broadleaf Forest, deciduous broadleaf), EBF (Evergreen Broadleaf Forest, evergreen broadleaf), MF (Mixed Forest), CRO (croland, farmland), GRA (Grassland), WET (Wetland), OSH (Open shrub and), and SAV (Savanna, tropical Grassland), respectively, and in addition, the simulated net ecosystem productivity data at the eight-day scale, month-scale, or year can be accumulated, compared with the measured net ecosystem productivity at the corresponding scale, and the performance of the model is observed at different scales.
The method constructs a calculation method of net ecosystem productivity based on a TL-LUE-NEP model based on widely used TL-LUE and TP models, collects daily-scale meteorological data in FLUXNET2015 sites and sites with complete actual measured net ecosystem productivity data, and corrects and verifies parameters through the sitesThe method comprises the steps of carrying out a first treatment on the surface of the The method for estimating the net ecological system productivity has higher precision, the whole method is simple and easy to operate, the parameters are fewer, the data are easy to obtain, an effective method is provided for quantifying regional carbon absorption, and reliable reference data is provided for regional carbon balance and measuring the carbon source/sink effect.
The foregoing is merely a preferred embodiment of the present invention and it should be noted that modifications and adaptations to those skilled in the art may be made without departing from the principles of the present invention, which are intended to be comprehended within the scope of the present invention.
Claims (10)
1. A method for calculating net ecosystem productivity, comprising the steps of:
s1: constructing a TL-LUE-NEP model according to a NEP=GPP-Re relation;
s2: selecting and correcting key parameters in TL-LUE-NEP model；
S3: collecting and processing required data;
s4: correcting and verifying parameters on siteAccuracy of (2);
s5: and comprehensively evaluating the effect of the model and the correction on the site scale.
2. A method of calculating net ecosystem productivity according to claim 1, wherein: in step S1, a TL-LUE model and a TP model are selected to construct a TL-LUE-NEP model, the TL-LUE model and the TP model respectively generate total primary productivity and ecosystem respiration, and NEP is obtained according to the relationship of NEP=GPP-Re;
where GPP is total primary productivity, re is ecosystem respiration, NEP is net ecosystem productivity.
3. A method of calculating net ecosystem productivity according to claim 1, wherein: in step S2, in order to facilitate the subsequent region simulation, the LAI product is used as input data, and parameters related to LAI in the model need to be correctedParameter correction is according to the formula:
；
where m is the number of all measured values,and->Estimated and measured net ecosystem productivity, respectively; />Is the average of the net ecosystem productivity measured; according to this formula, the stations involved in the correction are all optimized +.>。
4. A method of calculating net ecosystem productivity according to claim 1, wherein: in step S3, collecting daily weather data and sites with complete actual measured net ecosystem productivity data in the FLUXNET2015 site, checking whether the data are defective, if data of more than two months in one year are missing, deleting the data of the site in the year, interpolating missing data of less than two months in one year, and finally ensuring complete required data of the site.
5. The method of calculating net ecosystem productivity according to claim 4, wherein: in step S3, the LAI of the site is extracted from the LAI product according to the longitude and latitude of the required site, and the maximum LAI of the site in one year is considered as LAImax data, and the LAI data is used as input data to participate in correction.
6. A method of calculating net ecosystem productivity according to claim 1, wherein: in the step S4, classifying all sites according to vegetation types, randomly calculating 3/4 sites in each vegetation type for correction, and 1/4 sites for verification; finally, 79 sites were used for parameter correction and 24 sites were used for parameter verification.
7. A method of calculating net ecosystem productivity according to claim 6, wherein: in step S4, 79 site pairs are utilized for parametersCorrection is performed, the parameter correction range is set to 0.001-4, and each site will obtain an optimum +.>Values.
8. A method of calculating net ecosystem productivity according to claim 6, wherein: in step S4, the parameters are verified: optimal +.>And (5) sorting and averaging according to vegetation types, and then carrying the parameter average value of each vegetation type into a model for simulation.
9. A method of calculating net ecosystem productivity according to claim 1, wherein: in step S5, use is made ofAnd RMSE evaluation of the accuracy of modeling the net ecosystem productivity, +.>And the calculation formulas of RMSE are respectively:
；
；
where n is the number of measurement data,、/>estimating and measuring net ecosystem productivity data respectively; />Is an average value of estimated net ecosystem productivity data,/->Is the average value of the actual measurement net ecological system productivity data; and calculating the slope and intercept between the simulated net ecological system productivity and the actual ecological system productivity by using linear regression, and further evaluating the performance of the simulated net ecological system productivity.
10. A method of calculating net ecosystem productivity according to claim 9, wherein: in step S5, simulated net ecosystem productivity data of eight days, months or years may also be accumulated, and compared with actual measured net ecosystem productivity at the corresponding scale, the performance of the model at different scales may be observed.
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