CN-121995035-A - Multi-parameter real-time detection method and system for farmland carbon-water coupling process

CN121995035ACN 121995035 ACN121995035 ACN 121995035ACN-121995035-A

Abstract

The invention provides a farmland carbon-water coupling process multi-parameter real-time detection method and system, and relates to the technical field of agricultural ecological monitoring. According to the invention, soil CO 2 flux, soil moisture, soil temperature and microclimate data are obtained by arranging multi-parameter monitoring units in a test area, a synchronous multi-source real-time sequence is constructed, and quality control data are formed through abnormal elimination and missing measurement and filling. And extracting the carbon flux and water circulation characteristics based on the sliding time window, calculating a carbon-water response coefficient and a lag time, and constructing a carbon-water coupling index to realize real-time identification of the strong coupling, weak coupling and decoupling regions. The method realizes continuous, quantitative and real-time monitoring of the farmland carbon-water process.

Inventors

GAO CHAO
YUAN CHENGUANG
YANG JIANBO
FAN PENG
TIAN MENG
LI WENQIAN
WANG GUOBING
GUO LILI
LI DI
ZHANG SHIKE
TIAN YAN

Assignees

河南省科学院地理研究所

Dates

Publication Date: 20260508
Application Date: 20260310

Claims (8)

1. A farmland carbon-water coupling process multi-parameter real-time detection method is characterized by comprising the following steps: A multi-parameter monitoring unit capable of simultaneously acquiring soil CO 2 flux, soil moisture content, soil temperature and canopy microclimate elements is arranged in a farmland test area so as to continuously acquire original monitoring data of a carbon-water process; Synchronously collecting the original monitoring data according to the same time interval, and correspondingly forming a multi-source real-time data sequence by using the soil CO 2 flux monitoring data, the soil moisture monitoring data and the microclimate monitoring data as the same time sequence; based on the multi-source real-time data sequence, removing abnormal data and supplementing short-time missing test data to form a quality-controlled data sequence for carbon-water coupling analysis; Calculating the rate of change of the soil CO 2 flux and the daily accumulated CO 2 flux according to the quality control data sequence in a sliding time window to form a carbon flux characteristic parameter; in the sliding time window, calculating the change quantity of the soil water reserves and the evapotranspiration intensity according to the quality control data sequence to form a water circulation characteristic parameter; And calculating a carbon-water response coefficient and response lag time according to the carbon flux characteristic parameter and the water circulation characteristic parameter, constructing a carbon-water coupling index, and identifying a strong coupling area, a weak coupling area and a decoupling area according to the change of the carbon-water coupling index in a continuous time window so as to realize real-time detection of a farmland carbon-water coupling process.
2. The method for multi-parameter real-time detection of a carbon-water coupling process in a farmland according to claim 1, wherein a multi-parameter monitoring unit capable of simultaneously acquiring soil CO 2 flux, soil moisture content, soil temperature and canopy microclimate elements is arranged in a farmland test area to continuously acquire original monitoring data of the carbon-water process, comprising: Determining the layout position and the vertical sensing depth of the multi-parameter monitoring unit according to the physical and chemical differences of soil and the vegetation canopy structure in the farmland test area, so that the multi-parameter monitoring unit can cover the environmental gradients of the soil surface layer, the root zone layer and the canopy air layer at the same time; Configuring a multi-source sensing component for representing carbon flux, moisture dynamics and canopy microclimate elements in the multi-parameter monitoring unit, and establishing a cooperative sensing system taking uniform space positioning and continuous physical response as constraints; And performing background correction and dimension regulation processing on the output signals of the multi-source sensing component to obtain the original monitoring data capable of reflecting the soil respiration, moisture migration and canopy exchange process.
3. The method for multi-parameter real-time detection of a farmland carbon-water coupling process according to claim 1, wherein the original monitoring data are synchronously collected at the same time interval, and the soil CO 2 flux monitoring data, the soil moisture monitoring data and the microclimate monitoring data are correspondingly in the same time sequence to form a multi-source real-time data sequence, comprising: Triggering the cooperative acquisition operation of a soil CO 2 flux monitoring unit, a soil moisture monitoring unit and a microclimate monitoring unit in the multi-parameter monitoring unit according to a preset uniform sampling time interval, so that different monitoring amounts generate corresponding data at the same acquisition time; carrying out index association on soil CO 2 flux monitoring data, soil moisture monitoring data and microclimate monitoring data which are acquired at each acquisition time according to the acquisition time to generate a synchronous time sequence record corresponding to multiple parameters; constructing the multi-source real-time data sequence for characterizing dynamic changes of the carbon-water process based on the synchronous time sequence record.
4. The method of claim 1, wherein based on the multi-source real-time data sequence, removing anomaly data and supplementing short-term missing data to form a quality-controlled data sequence for carbon-water coupling analysis, comprising: Carrying out consistency test and fluctuation constraint analysis on soil CO 2 flux monitoring data, soil moisture monitoring data and microclimate monitoring data in the multisource real-time data sequence so as to judge abnormal data deviating from a normal change rule; Removing the judged abnormal data, and generating supplementary data according to the cooperative response relation between the change trend of the adjacent effective data and the similar monitoring amount in the period of lack of monitoring; And reconstructing the monitoring data after abnormal removal and deficiency compensation measurement into a continuous quality control data sequence.
5. The method for real-time detection of multiple parameters in a farmland carbon-water coupling process according to claim 4, wherein the generation formula of the complement data is: ; Wherein, the To be at the moment in the period of lack of measurement Monitoring the amount of targets The generated complement data; based on the target monitoring amount Linear interpolation is carried out on observed values of adjacent effective moments before and after the time-lacking period to obtain a trend estimated value; For monitoring the amount of targets Long term average during training phase or baseline statistics phase; For monitoring the amount of targets Standard deviation at the stage; to monitor the quantity with the target Similar monitoring of carbon-water process cooperative response relationship At the moment of time Is a measurement of the observed value of (2); for the same kind of monitoring quantity A long term average at the stage; for the same kind of monitoring quantity Standard deviation at the stage; to monitor the quantity with the target A similar monitoring quantity set with obvious cooperative response relation exists; For calculating target monitoring quantity according to historical quality control data sequence in training stage And the same kind of monitoring quantity Correlation coefficients between; for the moment of surrounding Target monitoring amount of (2) The length of the corresponding missing measurement zone; A time scale factor for controlling the relative contribution of the trend term and the collaborative response term.
6. The method of claim 1, wherein calculating the soil moisture reserves and the evapotranspiration intensity from the quality-controlled data sequence within the sliding time window to form the moisture cycle characteristic parameters comprises: Based on the quality-controlled data sequence, discrete layer accumulation is carried out on the soil volume moisture content of the root zone in a sliding time window, and the moment is calculated Is of the soil moisture reserves of (2) And obtain the starting time of sliding time window Reference soil moisture reserve variation The soil moisture reserves satisfy: wherein, the method comprises the steps of, For the moment of time Is a soil moisture reserve of (1); For starting moment of sliding time window A water reserve variation of (2); For the moment of time First, the The mass of each soil layer controls the volume water content; Is the first The thickness of each soil layer; The number of discrete layers of the soil layer; is the sliding time window length; Calculating an average evaporative intensity for the sliding time window based on the temporal sequence of instantaneous evaporative fluxes within the sliding time window The method comprises the following steps: wherein, the method comprises the steps of, The average evaporation intensity corresponding to the sliding time window; For the moment of time Is a transient evapotranspiration flux; Is a sampling time interval; The sampling time number in the sliding time window; Changing the water reserve of the soil With the intensity of the evapotranspiration The combination is used for constructing the water circulation characteristic parameter which can reflect the common driving mechanism of the water consumption of the root zone and the atmospheric evaporation.
7. The method for real-time detection of multiple parameters in a carbon-water coupling process in a farmland according to claim 1, wherein the method for real-time detection of a carbon-water coupling process in a farmland is characterized by calculating a carbon-water response coefficient and a response lag time according to the carbon flux characteristic parameter and the moisture circulation characteristic parameter, constructing a carbon-water coupling index, and identifying a strong coupling region, a weak coupling region and a decoupling region according to the change of the carbon-water coupling index in a continuous time window, and comprises the following steps: in the sliding time window, carrying out time sequence pairing on the carbon flux characteristic parameter sequence and the water circulation characteristic parameter sequence in the same sliding time window, and starting each sliding time window The extraction length is Is a carbon flux-characterized subsequence of (2) With water circulation characteristic subsequence Constructing a combined characteristic sequence for representing the cooperative change relation between the carbon flux change and the water circulation state; calculating a carbon-water response coefficient and a carbon-water response lag time within each of the sliding time windows based on the joint feature sequences, wherein the carbon-water response coefficient The method meets the following conditions: And a carbon-water response lag time The method meets the following conditions: wherein, the method comprises the steps of, For starting moment of sliding time window A corresponding carbon-water response coefficient; a lag time for the carbon-water response within the sliding time window; Is the first in the sliding time window Quality control value of the carbon flux characteristic parameters at each sampling moment; Is the first in the sliding time window Quality control value of the water circulation characteristic parameters at each sampling moment; for the characteristic subsequence of carbon flux in the current sliding time window Average value of (2); sub-sequence of features for moisture cycling within a current sliding time window Average value of (2); for the characteristic subsequence of carbon flux in the current sliding time window Standard deviation of (2); sub-sequence of features for moisture cycling within a current sliding time window Standard deviation of (2); the number of sampling moments contained in the sliding time window; Discrete time offsets for characterizing the carbon flux characteristics relative to the moisture cycling characteristics; An upper limit on the maximum discrete steps for the lag time search; Constructing a carbon-water coupling index by taking the carbon-water response coefficient and the carbon-water response lag time as inputs, classifying and identifying farmland carbon-water coupling processes according to changes of the carbon-water coupling index in a continuous time window, wherein the carbon-water coupling index is a natural energy value of the farmland carbon-water coupling process The method meets the following conditions: wherein, the method comprises the steps of, For starting moment of sliding time window A corresponding carbon-water coupling index; for the length of the sliding time window; the absolute value of the carbon-water response coefficient is used for representing the correlation strength of the carbon flux characteristic and the moisture circulation characteristic; The method is characterized by comprising the steps of determining a time mismatch degree of carbon-water interaction, determining a time mismatch degree of carbon-water response lag time, determining a strong coupling region when the carbon-water coupling index is stably kept at a high level, determining a weak coupling region when the carbon-water coupling index is at a medium level and fluctuates greatly, and determining a decoupling region when the carbon-water coupling index is continuously lower than a preset threshold value in a continuous time window, so that real-time detection of a farmland carbon-water coupling process is realized.
8. A farmland carbon-water coupling process multi-parameter real-time detection system is characterized by comprising: The multi-parameter monitoring unit layout module is used for setting a multi-parameter monitoring unit capable of simultaneously acquiring soil CO 2 flux, soil moisture content, soil temperature and canopy microclimate elements in a farmland test area so as to continuously acquire original monitoring data of a carbon-water process; The multi-source data synchronous acquisition module is used for synchronously acquiring the original monitoring data according to the same time interval, and correspondingly integrating the soil CO 2 flux monitoring data, the soil moisture monitoring data and the microclimate monitoring data into the same time sequence to form a multi-source real-time data sequence; The data quality control module is used for removing abnormal data and supplementing short-time missing test data based on the multi-source real-time data sequence to form a quality control data sequence for carbon-water coupling analysis; The carbon flux characteristic calculation module is used for calculating the soil CO 2 flux change rate and the daily accumulated CO 2 flux according to the quality control data sequence in a sliding time window to form a carbon flux characteristic parameter; The water circulation characteristic calculation module is used for calculating the change quantity of the soil water reserves and the evapotranspiration intensity according to the quality control data sequence in the sliding time window to form a water circulation characteristic parameter; And the carbon-water coupling analysis and section identification module is used for calculating a carbon-water response coefficient and response lag time according to the carbon flux characteristic parameter and the water circulation characteristic parameter, constructing a carbon-water coupling index, and identifying a strong coupling area, a weak coupling area and a decoupling area according to the change of the carbon-water coupling index in a continuous time window so as to realize real-time detection of a farmland carbon-water coupling process.

Description

Multi-parameter real-time detection method and system for farmland carbon-water coupling process Technical Field The invention relates to the technical field of agricultural ecological monitoring, in particular to a farmland carbon-water coupling process multi-parameter real-time detection method and system. Background Under the global climate change and the 'double carbon' target background, the farmland ecological system is used as an important land carbon sink, and the soil carbon fixing capability and the response to moisture circulation factors such as precipitation patterns, evapotranspiration processes and the like are attracting more and more attention. In the existing research, the static box method and the vorticity related system are used for monitoring the farmland CO 2 flux, and the farmland carbon balance condition can be described to a certain extent by combining the soil moisture, temperature and meteorological observation, so that support is provided for evaluating the farmland carbon balance function. Meanwhile, with the development of the Internet of things and the low-power consumption sensor, the soil moisture, meteorological elements and the like of the farmland environment can be automatically collected at a higher frequency, and a data basis is provided for analyzing the farmland moisture circulation process. The current technology development trend is that based on multisource monitoring data, carbon circulation and moisture circulation are expanded from single element observation to multi-element collaborative observation, and a data fusion and model analysis method is tried to be adopted, so that the coupling relation between farmland carbon-water processes is revealed from two scales of time sequence and space pattern. On one hand, a plurality of sensors such as soil moisture, temperature, CO 2 flux and the like are distributed on the field scale, continuous monitoring is realized by combining a meteorological tower with precipitation monitoring, on the other hand, methods such as sliding time window analysis, correlation analysis, structural equation and the like are introduced, influence mechanisms of precipitation events, soil moisture alternation, irrigation management and the like on the soil carbon fixing process are explored, and quantitative basis is provided for farmland water and fertilizer management optimization and carbon fixing and collection increase. However, the prior art has the following defects that firstly, most monitoring systems still set carbon flux observation and moisture parameter observation independently, only univariate statistics is carried out on carbon flux or moisture state, a multiparameter real-time detection framework facing a carbon-water coupling process is constructed under a unified time reference and space unit, dynamic response of a carbon fixing process to instantaneous precipitation or short-term drought is difficult to identify in time, secondly, even if multisource observation is arranged, correlation analysis is often carried out only on a long-term statistical scale, coupling characteristic parameters such as response coefficient, lag time and the like in a sliding time window are not constructed aiming at non-stationarity of farmland carbon-water relationship, and the coupling strength change is not characterized in different cultivation measures and extreme climate conditions, thirdly, the prior art system attaches more importance to real-time display and early warning on single variables, and has insufficient construction and space-time diagnosis capability on the carbon-water coupling index, and response mechanism of a soil carbon fixing process to moisture circulation disturbance cannot be directly revealed. Therefore, it is necessary to provide a farmland carbon-water coupling process multi-parameter real-time detection method for realizing real-time detection and space-time diagnosis of the carbon-water coupling process by uniformly distributing multi-parameter sensing networks on the farmland scale so as to make up for the defects of the prior art in the aspects of quantitative characterization and real-time identification of the coupling relation. Disclosure of Invention In order to overcome the defects of the prior art, the invention aims to provide a farmland carbon-water coupling process multi-parameter real-time detection method and system, and continuous, quantitative and real-time accurate detection of the farmland carbon-water process which cannot be achieved by the prior art is realized by constructing a multi-parameter collaborative monitoring, time sequence unified data quality control system and a carbon-water coupling index based on response coefficient and hysteresis identification. In order to achieve the above object, the present invention provides the following solutions: A farmland carbon-water coupling process multi-parameter real-time detection method comprises the following steps: A multi-parameter moni