CN-122022201-A - Quantitative evaluation decision method and system for soil acidification treatment effect

CN122022201ACN 122022201 ACN122022201 ACN 122022201ACN-122022201-A

Abstract

The invention relates to the technical field of environmental treatment project supervision and prediction and discloses a quantitative evaluation decision method and a quantitative evaluation system for soil acidification treatment effect, wherein the quantitative evaluation decision method comprises the steps of obtaining a system state variable sequence and an external disturbance intensity parameter of discrete nodes of a treatment project, extracting an intrinsic loss coefficient of a stress-resistant buffer system of a treatment object by calculating a state variable transition rate and utilizing a steady-state weight factor to counter extrinsic fluctuation, deducing an effect attenuation prediction data chain to calculate a risk time allowance, establishing an intervention priority mapping relation, updating a treatment resource reset to a scheduling matrix, and generating a financial budget and treatment force throwing instruction.

Inventors

QIAN XIAOJIE
CHEN JIAWEI
JIANG YUYING
ZHANG SHICHANG
CHEN WENSHENG
XIAO QINGTIE
ZHENG XIANGZHENG
LIU YUQIAN
LIN YINGSHENG

Assignees

福建农业职业技术学院

Dates

Publication Date: 20260512
Application Date: 20260414

Claims (9)

1. The quantitative evaluation decision-making method for the soil acidification treatment effect is characterized by comprising the following steps of: Step S101, acquiring a system state variable sequence of an environmental treatment project at a plurality of discrete time nodes and external disturbance intensity parameters corresponding to each discrete time node, wherein the system state variable sequence comprises a hydrogen ion activity characterization quantity, an organic matter capacity and an exchangeable cation capacity; step S102, calculating the transition rate of a system state variable sequence between adjacent time nodes, correcting the transition rate by using a system steady-state weight factor, and countering extrinsic numerical fluctuation caused by external disturbance intensity parameters to extract intrinsic break coefficients reflecting the degradation state of a stress-resistant buffer system of a treatment engineering object; Step S103, based on the intrinsic loss coefficient, deducing an efficiency attenuation prediction data chain of the environmental treatment project on a time axis, performing collision matching on the efficiency attenuation prediction data chain and a preset safety threshold, calculating a prediction time point when the efficiency attenuation prediction data chain touches the preset safety threshold, and extracting a time allowance representing treatment effect failure risk; Step S104, a monotonically decreasing mapping relation between the time allowance and the intervention priority weight is established, a resource allocation sequence of the treatment resource reset to the scheduling matrix is updated according to the monotonically decreasing mapping relation, the resource allocation sequence defines the financial money dialing priority and engineering material configuration proportion of each supervision unit in a preset treatment period, and a scheduling instruction aiming at the total budget amount and the treatment force input in the administrative management system is generated.
2. The quantitative evaluation decision method for soil acidification treatment effect according to claim 1 is characterized in that the logic for generating the external disturbance intensity parameter in the step S101 is that in the step S1011, the accumulated precipitation amount and the artificial intervention frequency of the environmental treatment project are collected, the artificial intervention frequency is mapped into acid neutralization capacity load equivalent according to a preset intensity level, and in the step S1012, the diffusion intensity correction is carried out on the acid neutralization capacity load equivalent according to the accumulated precipitation amount, and a scalar representing the total external disturbance intensity is generated as the external disturbance intensity parameter.
3. The quantitative evaluation decision method for soil acidification treatment effect according to claim 1, wherein the sampling period of the system state variable sequence obtained in step S101 is not less than 90d, and the sampling environmental humidity deviation of each discrete time node is less than 15%.
4. The quantitative evaluation decision method for soil acidification treatment effect according to claim 1 is characterized in that the logic for correcting the transition rate by using the system steady-state weight factor in the step S102 is that a system steady-state weight factor reference value is set according to the initial physical texture duty ratio of an environmental treatment project in the step S1021, and the transition rate is divided by the product of the system steady-state weight factor reference value and an external disturbance intensity parameter in the step S1022 to complete linear decoupling denoising of the transition rate.
5. The quantitative evaluation decision method for soil acidification treatment effect according to claim 1 is characterized in that the method for calculating the predicted time point in the step S103 is that in the step S1031, a Markov state transition probability matrix is applied to simulate a state drift track of an environmental treatment project under the effect of an intrinsic fracture coefficient, and in the step S1032, when a predicted value of the state drift track is coincident with a preset safety threshold, a corresponding time abscissa is extracted as the predicted time point.
6. The quantitative evaluation decision-making method for soil acidification treatment effect according to claim 1, wherein the criterion for establishing the mapping relation between the time margin and the intervention priority weight in the step S104 is that the shorter the time margin is, the higher the corresponding intervention priority weight is, and when the time margin is lower than a preset management warning time limit, the response slope of the intervention priority weight is regulated and increased by a preset emergency factor.
7. The quantitative evaluation decision method for soil acidification treatment effect according to claim 1, wherein the process of updating the treatment resource reset to the scheduling matrix in step S104 comprises the steps of arranging the intervention priority weights of the plurality of evaluation grids in descending order to generate an administrative decision priority sequence, and allocating the treatment resource shares from the top of the administrative decision priority sequence downwards in order according to the total budget amount in the administrative management system in step S1042.
8. The method of claim 1, further comprising the steps of S105, monitoring feedback values of system state variables after dispatching instructions, and if the feedback values have a rate of return within two consecutive sampling periods lower than a preset reference, re-triggering steps S102 to S104 to correct weight distribution factors in the dispatching instructions, wherein the environmental management project is divided into a plurality of supervision units with independent administrative numbers, and each supervision unit independently applies steps S101 to S104 to determine an asymmetric refined dispatching scheme for managing resources in the management system.
9. A soil acidification treatment success rate quantitative assessment decision system for implementing a soil acidification treatment success rate quantitative assessment decision method according to claim 1, comprising: The data acquisition module is used for acquiring a system state variable sequence of the environmental treatment project at a plurality of discrete time nodes and external disturbance intensity parameters corresponding to the discrete time nodes; the intrinsic analysis module is used for calculating the transition rate of the system state variable sequence between adjacent time nodes, and correcting the transition rate by applying a system steady-state weight factor so as to extract an intrinsic break coefficient reflecting the degradation state of the stress-resistant buffer system of the treatment engineering object; The risk prediction module is used for deducing an efficacy attenuation prediction data chain of the environmental treatment project on a time axis based on the intrinsic loss coefficient, and extracting a time allowance representing the treatment effect failure risk by matching the efficacy attenuation prediction data chain with a preset safety threshold; The decision scheduling module is used for establishing a monotonically decreasing mapping relation between the time allowance and the intervention priority weight, updating a resource allocation sequence of treatment resource reset to the scheduling matrix according to the monotonically decreasing mapping relation, and generating a scheduling instruction aiming at the total budget amount and the treatment power release in the administrative management system.

Description

Quantitative evaluation decision method and system for soil acidification treatment effect Technical Field The invention relates to a quantitative evaluation decision method and a quantitative evaluation decision system for soil acidification treatment effect, and belongs to the technical field of environmental treatment project supervision and prediction. Background The method is characterized in that a static comparison technology based on discrete nodes is generally adopted at present, the pH value and organic matter content data of a treatment starting and checking and accepting stage are obtained, standard conditions are evaluated according to numerical value difference values, the standard conditions are used as the basis for giving an evaluation report and giving a checking and accepting instruction, the stress resistance stability of a complex environment system is determined by an endogenous buffer capacity and an exogenous disturbance load, the treatment investment is essentially that a chemical buffer capacity is restored, however, an existing comparison framework takes a target land block as a static evolution object, the hysteresis attenuation law of environmental interference prognosis is ignored, and when the system is in complex working conditions such as a large-area agricultural land or an ecological restoration area, the evaluation flow often covers the rebound risk of efficiency, so that the supervision resource delivery deviates from an actual attenuation curve. In order to improve the monitoring precision, a method of increasing sampling frequency or introducing multidimensional variable modeling is generally adopted, because a great amount of random noise interference exists in an agricultural production environment and the cost of on-site high-frequency sampling is high, the transient data fluctuation caused by precipitation or fertilization cannot be effectively stripped by the linear improvement method, therefore, the intrinsic index representing the degradation rule of treatment effectiveness is difficult to extract from low-frequency sampling data by the traditional scheme, for example, the Chinese patent application with the publication number of CN121072957A discloses an orchard acidification soil improvement effect evaluation system based on a knowledge graph, the improvement intensity is quantified by constructing a dynamic knowledge graph and utilizing a causal reasoning model, but in an actual administrative supervision scene, the technical logic is highly dependent on continuous time sequence data provided by a sensor network, and the linear decoupling capability of strong random external interference such as rainfall and fertilization is lacked, the intelligent method is difficult to strip transient environment noise from low-frequency sampling data, the intrinsic degradation rule reflecting the real stress state of a treated land block cannot be accurately extracted, the problem that the prior art has a plurality of steps in the effect evaluation level cannot be established from the land block attenuation potential to the reset to the administration of an administrative resource, and the problem of the mapping of the administrative resource is difficult to be solved. Therefore, how to determine the intrinsic loss law of the treatment efficiency according to the discrete data and adjust the resource scheduling matrix according to the intrinsic loss law, so as to realize the precise alignment of the administrative management instruction and the land block degradation risk, and the invention is a technical problem to be solved. Disclosure of Invention In order to solve the problems in the background technology, the technical scheme of the invention is as follows, a quantitative evaluation decision method for soil acidification treatment effect comprises the following steps: Step S101, acquiring a system state variable sequence of an environmental treatment project at a plurality of discrete time nodes and external disturbance intensity parameters corresponding to each discrete time node, wherein the system state variable sequence comprises a hydrogen ion activity characterization quantity, an organic matter capacity and an exchangeable cation capacity; step S102, calculating the transition rate of a system state variable sequence between adjacent time nodes, correcting the transition rate by using a system steady-state weight factor, and countering extrinsic numerical fluctuation caused by external disturbance intensity parameters to extract intrinsic break coefficients reflecting the degradation state of a stress-resistant buffer system of a treatment engineering object; Step S103, based on the intrinsic loss coefficient, deducing an efficiency attenuation prediction data chain of the environmental treatment project on a time axis, performing collision matching on the efficiency attenuation prediction data chain and a preset safety threshold, calculating a prediction time