Method for evaluating and analyzing influence of biodegradable mulching film on arid region field soil environment

Abstract

The invention discloses a method for evaluating and analyzing the influence of a biodegradable mulching film on an arid region field soil environment, and relates to the technical field of agricultural environment protection and soil management. The method comprises the following steps: acquiring soil environment data of the arid region through a sensor network, acquiring meteorological data through meteorological monitoring equipment, selecting a biodegradable mulching film, and applying the biodegradable mulching film to the soil of the arid region. And monitoring the physical properties of the soil and the chemical properties of the soil to generate physicochemical property data. According to the method, a multi-factor analysis model for soil environment data acquisition, meteorological data acquisition and soil physicochemical property monitoring is established, so that the influence of the biodegradable mulching film on the soil environment of the arid region is comprehensively analyzed. The degradation characteristic of the mulching film and the soil moisture retention effect are comprehensively analyzed through degradation rate evaluation and moisture retention ability testing, and a basis is provided for optimization of a soil improvement strategy in an arid region.

Description

Technical Field

[0001] This invention belongs to the field of agricultural environmental protection and soil management technology, and in particular relates to a method for evaluating and analyzing the impact of biodegradable mulch film on the soil environment in arid regions. Background Technology

[0002] Currently, biodegradable mulch films are mainly made of natural polymer materials or biodegradable polymers and possess self-degrading properties. They reduce the environmental pollution caused by traditional plastic mulch films, maintain soil moisture during the crop growing season, and reduce dependence on external climate change. In arid regions, the application of biodegradable mulch films can significantly improve water use efficiency and provide a stable growing environment for crops, and has been promoted globally.

[0003] Current technologies for the application of biodegradable mulch films and the assessment of their soil environmental impact still have some limitations. For example, in arid regions, existing technologies fail to adequately assess the long-term effects of mulch films on soil. In arid areas, soil management is complex, and simply detecting degradation products cannot comprehensively reflect the long-term impacts of mulch films on soil structure, fertility, and the microbial ecosystem. Furthermore, current technologies fail to effectively integrate soil characteristics and climatic factors in arid regions to comprehensively assess the long-term soil impacts of biodegradable mulch films.

[0004] To address these issues, we provide a method for evaluating and analyzing the impact of biodegradable mulch films on the soil environment in arid regions. Summary of the Invention

[0005] To address the shortcomings of existing technologies, this invention provides a method for evaluating and analyzing the impact of biodegradable mulch film on the soil environment in arid regions. The technical problem this invention aims to solve is: how to address the issue that existing technologies have failed to adequately assess the long-term impact of biodegradable mulch film on soil in arid regions through comprehensive soil data monitoring and multi-factor analysis.

[0006] This invention provides a method for evaluating and analyzing the impact of biodegradable mulch film on the soil environment in arid regions, comprising: S1. Collect soil environmental data in arid areas through sensor networks and acquire meteorological data through meteorological monitoring equipment; S2. Select a biodegradable mulch film, apply the biodegradable mulch film to the soil in the arid region, and monitor the physical and chemical properties of the soil to generate physicochemical property data; S3. Construct a multi-factor analysis model based on the soil environmental data and the meteorological data. The multi-factor analysis model performs a comprehensive analysis of the biodegradable mulch film to form a comprehensive evaluation result. The comprehensive analysis includes degradation rate analysis and water retention capacity test. S4. Based on the physicochemical property data, conduct an ecological adaptability assessment on the comprehensive assessment results, and form a soil environmental impact assessment result through the ecological adaptability assessment. The ecological adaptability assessment includes time series analysis and dynamic prediction model. S5. Based on the soil environmental impact assessment results, optimize the soil improvement strategy for the arid region, and formulate a biodegradable mulch film application strategy through the optimization of the soil improvement strategy.

[0007] The present invention is further configured such that the sensor network includes a soil moisture sensor, a soil temperature sensor, and a soil pH sensor, and the meteorological monitoring equipment includes an ambient temperature sensor, a precipitation sensor, and a wind speed sensor.

[0008] The present invention is further configured such that the physical properties include soil density, soil porosity and soil bulk density, and the chemical properties include soil nutrient content, soil pH value and soil electrical conductivity, and the physical properties and the chemical properties are measured simultaneously to form the physicochemical property data.

[0009] The present invention is further configured such that the degradation rate analysis is performed using a gas chromatography-mass spectrometry (GC-MS) instrument, the GC-MS instrument measures the concentration of the biodegradable mulch film, the degradation rate of the biodegradable mulch film is evaluated based on the concentration measurement, and a degradation rate evaluation result is formed through the degradation rate evaluation.

[0010] The present invention is further configured such that the water retention capacity test adopts an evaporation rate testing device, the evaporation rate testing device measures the soil moisture evaporation rate, the water retention effect of the biodegradable mulch film is measured based on the measurement, a water retention effect evaluation result is formed through the water retention effect measurement, and the degradation rate evaluation result and the water retention effect evaluation result are weighted and summarized to form the comprehensive evaluation result.

[0011] The present invention is further configured such that the time series analysis method performs trend analysis on the comprehensive evaluation results based on the physicochemical property data, and forms time series data through the trend analysis; the dynamic prediction model performs long-term change prediction on the time series data to form the soil environmental impact assessment results; and the long-term change prediction adopts the Long Short-Term Memory Network algorithm.

[0012] The present invention is further configured such that the trend analysis includes the following steps: S41. The comprehensive evaluation results are weighted and averaged based on the physicochemical property data, and a basic time pattern is formed by the weighted average. S42. Perform periodic fluctuation analysis on the aforementioned basic time pattern to form a periodic pattern; S43. Extract the time window from the periodic pattern to form the time series data.

[0013] The present invention is further configured such that the model formula of the Long Short-Term Memory network algorithm is: .

[0014] in, The soil environmental impact assessment result at time t is dimensionless. The time series data, after normalization, becomes dimensionless. The prediction output of the i-th Long Short-Term Memory network for the time series data is dimensionless. The parameter set of the Long Short-Term Memory network, after normalization, is dimensionless. These are weighting coefficients, dimensionless. It is an integrated function and is dimensionless.

[0015] The present invention is further configured such that the soil improvement strategy optimization includes nutrient management and water management, wherein the nutrient management is based on the soil environmental impact assessment results to supplement the arid area with target nutrients, and the target nutrient supplementation is achieved by adjusting the soil nutrient content through precise fertilization.

[0016] The present invention is further configured such that the water management is based on the soil environmental impact assessment results to regulate water irrigation in the arid region, the water irrigation regulation adopts drip irrigation technology, and the synergistic effect of the target nutrient supplementation and the water irrigation regulation forms the biodegradable mulch film application strategy.

[0017] The beneficial effects of this invention are as follows: This invention comprehensively analyzes the impact of biodegradable mulch film on the soil environment in arid regions by establishing a multi-factor analysis model that integrates soil environmental data collection, meteorological data acquisition, and soil physicochemical property monitoring. Through degradation rate assessment and water retention capacity testing, the degradation characteristics and soil water retention effects of the mulch film are comprehensively analyzed, providing a basis for optimizing soil improvement strategies in arid regions.

[0018] A multi-factor analysis model, time series analysis, and long short-term memory network algorithm were used in synergy to conduct an in-depth assessment of soil environmental impacts, accurately predict long-term soil change trends, and optimize soil improvement strategies based on the analysis results. Precise regulation of nutrient and water management ultimately promoted the application of biodegradable mulch films, improving soil moisture retention capacity while simultaneously improving the soil environment. Attached Figure Description

[0019] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below.

[0020] Figure 1 A flowchart illustrating the overall workflow of a system for evaluating and analyzing the impact of biodegradable mulch film on the soil environment in arid regions.

[0021] Figure 2 This is a flowchart of a multi-factor analysis model used in the evaluation and analysis of the impact of biodegradable mulch film on the soil environment in arid regions.

[0022] Figure 3 A flowchart of the time series analysis and prediction model in the evaluation and analysis method of the impact of biodegradable mulch film on the soil environment in arid areas. Detailed Implementation

[0023] The technical solutions of the present invention will be described below with reference to the accompanying drawings. The described embodiments are only some embodiments of the present invention, and not all embodiments.

[0024] Example 1 Please see Figures 1-3 This invention provides a method for evaluating and analyzing the impact of biodegradable mulch film on the soil environment in arid regions, comprising: S1. Soil environmental data in arid regions is collected through a sensor network, and meteorological data is acquired through meteorological monitoring equipment. The sensor network includes soil moisture sensors, soil temperature sensors, and soil pH sensors, while the meteorological monitoring equipment includes ambient temperature sensors, precipitation sensors, and wind speed sensors.

[0025] S2. Select biodegradable mulch film and apply it to soils in arid regions. Monitor the physical and chemical properties of the soil to generate physicochemical data. Physical properties include soil density, soil porosity, and soil bulk density; chemical properties include soil nutrient content, soil pH, and soil electrical conductivity. Simultaneous measurement of physical and chemical properties generates physicochemical data.

[0026] S3. A multi-factor analysis model was constructed based on soil environmental and meteorological data. This model comprehensively analyzed the biodegradable mulch film to generate a comprehensive evaluation result. The comprehensive analysis included degradation rate analysis and water retention capacity testing. Degradation rate analysis employed gas chromatography-mass spectrometry (GC-MS) to determine the concentration of the biodegradable mulch film. Based on the concentration determination, the degradation rate of the biodegradable mulch film was evaluated, and a degradation rate assessment result was generated. Water retention capacity testing used an evaporation rate testing device to measure the soil moisture evaporation rate. Based on this measurement, the water retention effect of the biodegradable mulch film was determined, and a water retention effect assessment result was generated. The degradation rate assessment result and the water retention effect assessment result were weighted and summed to form a comprehensive evaluation result.

[0027] S4. Based on the physicochemical property data, conduct an ecological adaptability assessment of the comprehensive evaluation results. This assessment forms the soil environmental impact assessment result, which includes time-series analysis and a dynamic prediction model. The time-series analysis method performs trend analysis on the comprehensive evaluation results based on the physicochemical property data, generating time-series data. The dynamic prediction model then uses a long short-term memory network algorithm to predict long-term changes in this time-series data, forming the soil environmental impact assessment result. The long-term change prediction employs the long short-term memory network algorithm. The trend analysis includes the following steps: S41. The comprehensive evaluation results are weighted and averaged based on the physicochemical properties data, and a basic time pattern is formed by weighted averaging.

[0028] S42. Perform periodic fluctuation analysis on the basic time pattern to form a periodic pattern.

[0029] S43. Extract time windows from periodic patterns to form time series data.

[0030] The model formula for the Long Short-Term Memory (LSTM) network algorithm is as follows: .

[0031] in, The soil environmental impact assessment result at time t is dimensionless. The data is time series, and after normalization, it becomes dimensionless. The output of the i-th Long Short-Term Memory network for predicting time series data is dimensionless. The parameter set for the Long Short-Term Memory network is normalized to be dimensionless. These are weighting coefficients, dimensionless. It is an integrated function and is dimensionless.

[0032] S5. Based on the soil environmental impact assessment results, optimize soil improvement strategies for arid regions, and formulate a biodegradable mulch film application strategy through this optimization. Soil improvement strategy optimization includes nutrient management and water management. Nutrient management, based on the soil environmental impact assessment results, involves targeted nutrient supplementation in arid regions, which is achieved through precise fertilization to regulate soil nutrient content. Water management, based on the soil environmental impact assessment results, involves irrigation regulation in arid regions, employing drip irrigation technology. The synergistic effect of targeted nutrient supplementation and irrigation regulation forms the biodegradable mulch film application strategy.

[0033] The application of biodegradable mulch improves the physical properties of the soil, reduces soil compaction, increases soil porosity, and enhances soil permeability and aeration. This promotes plant root growth and improves the crop growing environment.

[0034] By testing the water retention capacity of biodegradable mulch films, we can reduce water evaporation, thereby decreasing soil moisture loss in arid regions and improving the soil's drought resistance.

[0035] The degradation process of biodegradable mulch film releases organic matter, improves soil nutrient structure, helps promote plant growth, and enhances soil fertility.

[0036] By combining time series analysis and dynamic prediction models to conduct ecological adaptability assessments, we can accurately predict long-term changes in the soil environment, provide a scientific basis for soil improvement decisions, address climate change, and optimize resource management.

[0037] By optimizing nutrient and water management schemes, we can precisely regulate the levels of nutrients and water in the soil, improve agricultural production efficiency in arid regions, and promote the development of precision agriculture and sustainable agriculture.

[0038] Biodegradable mulch film reduces the environmental pollution caused by traditional plastic mulch film and has good ecological and environmental benefits. The biodegradable nature of biodegradable mulch film prevents traditional mulch film from remaining in the soil for extended periods, thus reducing environmental pollution and resource waste.

[0039] Example 2 Please see Figure 2 Based on Example 1, the application effect of biodegradable mulch film in arid areas was evaluated, with a focus on analyzing its role in water retention and soil improvement. Specific implementation methods are as follows: This experiment was conducted in a typical arid region of Gansu Province, starting on June 1, 2025, and lasting for 21 days. The main objective was to assess the impact of biodegradable mulch films on the soil environment by measuring their degradation rate and water retention capacity.

[0040] 1. Data Collection Soil environmental data: Soil environmental data was collected in real time through an installed sensor network, with key parameters including soil moisture, soil temperature, and soil pH. Sophisticated environmental monitoring equipment was used in the experiment to ensure the accuracy and timeliness of data collection. Data was collected hourly.

[0041] Data acquisition equipment: Soil moisture sensor: A dry / wet sensor is used for real-time monitoring.

[0042] Soil temperature sensor: Samples are taken every 30 cm in depth, and the data is transmitted in real time via wireless network.

[0043] pH sensor: Measures every 6 hours.

[0044] Meteorological data: Meteorological data during the experiment were obtained from local meteorological monitoring stations, and the measurements included ambient temperature, precipitation and wind speed.

[0045] Table 1: Data Collection Table.

[0046] 2. Degradation rate analysis The degradation rate was determined using gas chromatography-mass spectrometry (GC-MS). Soil samples were collected every 7 days from the area where the plastic film was applied, and the concentration changes of the film were analyzed using GC-MS.

[0047] Measurement steps: Twenty soil samples were collected each week, with each sample weighing 500 grams.

[0048] Soil samples were mixed with biodegradable mulch film, and the concentration of degradation substances was detected using gas chromatography-mass spectrometry.

[0049] Table 2: Degradation rate data.

[0050] Degradation rate calculation, in mg / g∙d: From June 1st to June 7th: From June 7th to June 14th: From June 14th to June 21st: 3. Moisture retention capacity test The water retention capacity was tested using an evaporation rate testing device, which simulates the natural conditions of water evaporation in the soil. Evaporation rate measurements were taken every 3 days, including the amount of soil moisture evaporating from the soil covered with biodegradable mulch.

[0051] Evaporation ponds were set up in each experimental area, and the soil surface was covered with biodegradable mulch. The evaporation rate was measured every 3 days, and the daily evaporation data was recorded.

[0052] Table 3: Data on water evaporation rate.

[0053] 4. Comprehensive evaluation The degradation rate and water retention capacity assessment results were weighted and summarized. Weighting coefficients were set based on soil characteristics and meteorological conditions. In this experiment, the weighting coefficient for degradation rate was 60%, and the weighting coefficient for water retention capacity was 40%. That is, the weighting coefficient for degradation rate is: Weighting coefficients for moisture retention capacity: .

[0054] Comprehensive evaluation formula: Each indicator was normalized, and the degradation rate and water evaporation rate were weighted and calculated.

[0055] For data from June 1, 2025: the degradation rate was 3.33 mg / g·d, and the water evaporation rate was 0.20 mm / day. After normalization, the degradation rate was 1, and the water evaporation rate was 1.

[0056] For data from June 15, 2025: Degradation rate = 2.14 mg / g·d; Water evaporation rate = 0.12 mm / day. After normalization, the degradation rate is 0, and the water evaporation rate is 0. Overall assessment results: Through the above steps, the experimental results show that biodegradable mulch film significantly improved soil moisture retention capacity in arid regions, reducing the evaporation rate from 0.20 mm / day to 0.12 mm / day, demonstrating its moisture retention effect. However, the degradation rate of the mulch film gradually slowed down over time, decreasing from 3.33 mg / g·d to 2.14 mg / g·d, indicating that the degradation process of the mulch film gradually slowed down.

[0057] The comprehensive evaluation results indicate that although biodegradable mulch films perform well in the short term, the slowdown in their degradation rate may limit their long-term effectiveness. Therefore, it is recommended that their application in arid regions be combined with other soil improvement measures to enhance their long-term benefits.

[0058] Example 3 Please see Figure 3 Based on Examples 1 and 2, the changing trends of soil moisture, temperature, and pH were assessed using time-series analysis and an LSTM model, and long-term predictions were made using the model. The specific implementation method is as follows: 1. Data Collection Soil environmental data: Soil moisture, temperature, and pH data are collected in real time through the deployment of a sensor network. The following is the data collected from June 1st to June 15th, 2025: Table 4: Soil Environmental Data Collection Table.

[0059] Meteorological data: Meteorological data during the experiment were obtained from local meteorological monitoring stations. The following is the meteorological data from June 1 to June 15, 2025: Table 5: Meteorological Data Collection Table.

[0060] 2. Time series analysis method The basic temporal pattern was formed by calculating a weighted average of soil moisture, temperature, and pH data.

[0061] Regression analysis revealed that humidity is crucial for soil moisture retention in arid regions and typically has a significant impact on crop growth. Therefore, humidity has a relatively high weight. The effects of temperature and pH on the soil environment are more indirect compared to humidity. A weight of 0.5 was set for humidity, while the weights for temperature and pH were each set to 0.25.

[0062] Based on the data collected from June 1st to June 15th, 2025, the following results were calculated: Periodic fluctuation analysis: Fourier transform analysis of soil moisture data revealed a 7-day periodic fluctuation in soil moisture, indicating that soil moisture fluctuates periodically with seasonal changes.

[0063] Extraction of time series data: Based on the above weighted average and periodic fluctuation analysis, time series data were extracted. The following are soil moisture and temperature data from June 1st to June 15th, 2025: The soil moisture time series were 13.53%, 14.3%, 15.0%, and 16.0%. The soil temperature time series were 33.33℃, 33.5℃, 33.0℃, and 32.8℃. 4. Dynamic Prediction Model The dynamic prediction model uses long-term change prediction of time series data to form the soil environmental impact assessment results. The long-term change prediction adopts the Long Short-Term Memory Network algorithm.

[0064] Long Short-Term Memory (LSTM) network models are used to predict future soil moisture and temperature, with time-series data as input. The core of LSM networks is to capture long-term dependencies in time-series data.

[0065] Training of Long Short-Term Memory Network Models: The model was trained using time-series data from June 1 to June 15, 2025. During training, the model learned from the input soil moisture, temperature, and pH data, and output future soil moisture and temperature.

[0066] Application of the formula for Long Short-Term Memory (LSTM) network models: The model formula for the Long Short-Term Memory (LSTM) network algorithm is as follows: .

[0067] in, The soil environmental impact assessment result at time t is dimensionless. The data is time series, and after normalization, it becomes dimensionless. The output of the i-th Long Short-Term Memory network for predicting time series data is dimensionless. The parameter set for the Long Short-Term Memory network is normalized to be dimensionless. These are weighting coefficients, dimensionless. It is an integrated function and is dimensionless.

[0068] Normalized time series data: Soil moisture and temperature data are normalized to make the data dimensionless. The normalization formula is: Tests showed that soil moisture levels ranged from 12.5% ​​to 18.2% from June 1st to June 15th, 2025. Soil moisture as of June 1, 2025 was normalized: Long Short-Term Memory Network Model Calculation: After training with the Long Short-Term Memory (LSTM) network, the network output the following prediction results: Predicted humidity for June 16, 2025: 16.5%, normalized to 0.263.

[0069] Predicted temperature for June 16, 2025: 32.4℃, normalized to 0.82.

[0070] Weighted calculation: Based on the output of the Long Short-Term Memory network, the impact assessment results of the soil environment are calculated using a weighted ensemble function.

[0071] Regression analysis revealed that soil moisture had the greatest impact on the soil environment, thus assigning it a higher weight, while temperature had a relatively smaller impact. , The calculation process is as follows: 5. Evaluation and Results Analysis Ecological adaptability assessment results: Based on the prediction results of time series analysis and long short-term memory network models, combined with existing soil environmental data and meteorological data, the following long-term trends in soil environmental change are derived: Soil moisture will continue to increase over the next two weeks, indicating that the mulch film continues to be effective in improving soil moisture retention.

[0072] Soil temperature is expected to decrease slightly over the next two weeks, indicating that biodegradable mulch film has a certain buffering effect on soil temperature regulation.

[0073] suggestion: Based on the ecological adaptability assessment results, it is recommended to adjust fertilization and irrigation strategies in a timely manner when using biodegradable mulch film. Combining the long-term prediction results of the Long Short-Term Memory (LSTM) network model, farmers can adjust irrigation frequency according to increases in soil moisture and decreases in temperature, and apply precise fertilization as needed to ensure the soil environment remains optimal in the coming months.

[0074] In summary, the experimental results show that biodegradable mulch film enhances soil moisture retention in arid regions, increasing soil humidity and indicating that the film can slow down water evaporation. However, the degradation rate of the film gradually slows down over time, leading to a gradual weakening of its effectiveness. Predictions from a long short-term memory network model suggest that soil moisture is expected to continue increasing in the coming weeks, while soil temperature is expected to decrease slightly, indicating that biodegradable mulch film has strong adaptability to the soil environment. To ensure long-term benefits, appropriate agricultural management measures are still necessary.

[0075] The foregoing has only described certain exemplary embodiments of the present invention by way of illustration. Undoubtedly, those skilled in the art can modify the described embodiments in various ways without departing from the spirit and scope of the present invention. Therefore, the foregoing drawings and descriptions are illustrative in nature and should not be construed as limiting the scope of protection of the claims of the present invention.

Claims

1. Methods for evaluating and analyzing the impact of biodegradable mulch film on the soil environment in arid regions. Includes, characterized in that: S1. Collect soil environmental data in arid areas through sensor networks and acquire meteorological data through meteorological monitoring equipment; S2. Select a biodegradable mulch film, apply the biodegradable mulch film to the soil in the arid region, and monitor the physical and chemical properties of the soil to generate physicochemical property data; S3. Construct a multi-factor analysis model based on the soil environmental data and the meteorological data. The multi-factor analysis model performs a comprehensive analysis of the biodegradable mulch film to form a comprehensive evaluation result. The comprehensive analysis includes degradation rate analysis and water retention capacity test. S4. Based on the physicochemical property data, conduct an ecological adaptability assessment on the comprehensive assessment results, and form a soil environmental impact assessment result through the ecological adaptability assessment. The ecological adaptability assessment includes time series analysis and dynamic prediction model. S5. Based on the soil environmental impact assessment results, optimize the soil improvement strategy for the arid region, and formulate a biodegradable mulch film application strategy through the optimization of the soil improvement strategy.

2. The method for evaluating and analyzing the impact of biodegradable mulch film on the soil environment in arid areas according to claim 1, characterized in that: The sensor network includes soil moisture sensors, soil temperature sensors, and soil pH sensors, and the meteorological monitoring equipment includes ambient temperature sensors, precipitation sensors, and wind speed sensors.

3. The method for evaluating and analyzing the impact of biodegradable mulch film on the soil environment in arid areas according to claim 1, characterized in that: The physical properties include soil density, soil porosity, and soil bulk density, and the chemical properties include soil nutrient content, soil pH value, and soil electrical conductivity. The physical and chemical properties are measured simultaneously to form the physicochemical property data.

4. The method for evaluating and analyzing the impact of biodegradable mulch film on the soil environment in arid areas according to claim 1, characterized in that: The degradation rate analysis was performed using a gas chromatography-mass spectrometry (GC-MS) instrument. The GC-MS instrument was used to determine the concentration of the biodegradable mulch film. Based on the concentration determination, the degradation rate of the biodegradable mulch film was evaluated, and a degradation rate evaluation result was formed through the degradation rate evaluation.

5. The method for evaluating and analyzing the impact of biodegradable mulch film on the soil environment in arid areas according to claim 4, characterized in that: The moisture retention capacity test uses an evaporation rate testing device to measure the soil moisture evaporation rate. Based on the measurement, the moisture retention effect of the biodegradable mulch film is measured, and a moisture retention effect evaluation result is formed by the moisture retention effect measurement. The degradation rate evaluation result and the moisture retention effect evaluation result are weighted and summarized to form the comprehensive evaluation result.

6. The method for evaluating and analyzing the impact of biodegradable mulch film on the soil environment in arid areas according to claim 1, characterized in that: The time series analysis method performs trend analysis on the comprehensive assessment results based on the physicochemical property data, and forms time series data through the trend analysis. The dynamic prediction model performs long-term change prediction on the time series data to form the soil environmental impact assessment results. The long-term change prediction adopts the Long Short-Term Memory Network algorithm.

7. The method for evaluating and analyzing the impact of biodegradable mulch film on the soil environment in arid areas according to claim 6, characterized in that: The trend analysis includes the following steps: S41. The comprehensive evaluation results are weighted and averaged based on the physicochemical property data, and a basic time pattern is formed by the weighted average. S42. Perform periodic fluctuation analysis on the aforementioned basic time pattern to form a periodic pattern; S43. Extract the time window from the periodic pattern to form the time series data.

8. The method for evaluating and analyzing the impact of biodegradable mulch film on the soil environment in arid areas according to claim 6, characterized in that: The model formula for the Long Short-Term Memory (LSTM) network algorithm is as follows: ， in, The soil environmental impact assessment result at time t is given. For the time series data, This is the prediction output of the i-th Long Short-Term Memory network for the time series data. This is the parameter set of the Long Short-Term Memory network. These are the weighting coefficients. This is an integrated function.

9. The method for evaluating and analyzing the impact of biodegradable mulch film on the soil environment in arid areas according to claim 1, characterized in that: The optimized soil improvement strategy includes nutrient management and water management. The nutrient management is based on the soil environmental impact assessment results to supplement the arid areas with target nutrients. The target nutrient supplementation is achieved by adjusting the soil nutrient content through precise fertilization.

10. The method for evaluating and analyzing the impact of biodegradable mulch film on the soil environment in arid areas according to claim 9, characterized in that: The water management is based on the soil environmental impact assessment results to regulate water irrigation in the arid areas. The water irrigation regulation adopts drip irrigation technology. The synergistic effect of the target nutrient supplementation and the water irrigation regulation forms the biodegradable mulch film application strategy.

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