Artificial precipitation enhancement influence ecological analysis method and system based on regional dynamic matching

Abstract

The invention discloses a regional dynamic matching-based artificial precipitation enhancement influence ecological analysis method and system. The method comprises the following steps of: obtaining weather modification operation effect data and meteorological data; dynamically setting a target fan-shaped area and at least one floating comparison fan-shaped area in the upwind direction according to wind data of a-5 DEG C temperature layer of the weather modification operation site, and selecting an optimal comparison area in the at least one floating comparison fan-shaped area in the upwind direction based on the correlation of a historical rainfall sequence; performing non-randomized efficacy analysis and abnormal value elimination on the target fan-shaped region and the comparison region to obtain a precipitation enhancement effect value; and calculating the response delay of the NDVI to natural rainfall through Pearson correlation, establishing the correlation between the rainfall enhancement effect and the NDVI based on the response delay, and separating the independent contribution value of artificial rainfall enhancement to vegetation change through multiple regression residuals. The potential mode of the precipitation enhancement effect is identified in the complex data, and the purpose is to accurately evaluate the weather modification operation effect and the ecological response of the weather modification operation effect.

Description

Technical Field

[0001] The invention belongs to the technical field of ecological analysis of artificial rainfall effects, and in particular relates to an ecological analysis method and system of artificial rainfall effects based on regional dynamic matching. Background Art

[0002] Artificial rainfall has a significant effect in increasing precipitation, alleviating drought, and reducing forest fires. However, existing effect evaluation methods have problems such as low spatial and temporal resolution of data, relatively single evaluation methods, and lack of comprehensive analysis of the impact on ecological benefits. Summary of the invention

[0003] The present invention provides an ecological analysis method and system for artificial rainfall impact based on regional dynamic matching, which are used to solve the technical problems of low spatiotemporal resolution of data and relatively single evaluation method in existing effect evaluation methods.

[0004] In a first aspect, the present invention provides an ecological analysis method of artificial rainfall impact based on regional dynamic matching, comprising: Obtain human shadow operation effect data and meteorological data; Dynamically set a target sector area and at least one floating comparison sector area according to meteorological data of the human shadow operation location, and select an optimal comparison area in the at least one floating comparison sector area based on the correlation of historical precipitation sequences; Performing non-randomized efficacy analysis and outlier elimination on the target sector area and the comparison area to obtain a rainfall increase effect value, wherein the rainfall increase effect value includes a relative rainfall increase rate and an absolute rainfall increase amount, wherein the non-randomized efficacy analysis is applied to a sequence analysis test, a regional comparison analysis test, a double ratio analysis test, and a regional historical regression analysis test; The response lag of NDVI to natural precipitation was calculated by Pearson correlation, and the correlation between the rainfall enhancement effect value and NDVI was established based on the response lag. The independent contribution value of artificial rainfall enhancement to vegetation change was separated through multiple regression residuals.

[0005] In a second aspect, the present invention provides an artificial rainfall impact ecological analysis system based on regional dynamic matching, comprising: An acquisition module configured to acquire human shadow operation effect data and meteorological data; A selection module configured to dynamically set a target sector area and at least one floating comparison sector area according to meteorological data of a human shadow operation location, and select an optimal comparison area in the at least one floating comparison sector area based on the correlation of a historical precipitation sequence; An analysis module is configured to perform non-randomized efficacy analysis and outlier elimination on the target sector area and the comparison area to obtain a rainfall increase effect value, wherein the rainfall increase effect value includes a relative rainfall increase rate and an absolute rainfall increase amount, wherein the non-randomized efficacy analysis is applied to a sequence analysis test, a regional comparison analysis test, a double ratio analysis test, and a regional historical regression analysis test; The output module is configured to calculate the response lag of NDVI to natural precipitation through Pearson correlation, establish the correlation between the rainfall enhancement effect value and NDVI based on the response lag, and separate the independent contribution value of artificial rainfall to vegetation change through multiple regression residuals.

[0006] According to a third aspect, an electronic device is provided, comprising: at least one processor, and a memory communicatively connected to the at least one processor, wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can perform the steps of the method for ecological analysis of the impact of artificial rainfall enhancement based on regional dynamic matching according to any embodiment of the present invention.

[0007] In a fourth aspect, the present invention further provides a computer-readable storage medium having a computer program stored thereon. When the program instructions are executed by a processor, the processor is caused to execute the steps of the method for ecological analysis of the impact of artificial rainfall enhancement based on regional dynamic matching according to any embodiment of the present invention.

[0008] The artificial rain enhancement ecological analysis method and system based on regional dynamic matching in this application is to solve the problem that regional fixed and meteorological interference factors are difficult to separate in traditional evaluation methods, and to separate the contribution of artificial rain enhancement / snow enhancement to ecology. This method combines four non-randomized efficacy analyses with ecological benefit evaluation to construct a comprehensive evaluation system for artificial rain enhancement effects and ecological impacts. At the same time, the introduction of machine learning-based pattern recognition and AI anomaly detection can identify potential patterns of rain enhancement effects in complex data; it aims to accurately evaluate the effects of human shadow operations and their ecological responses (such as vegetation growth). BRIEF DESCRIPTION OF THE DRAWINGS

[0009] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0010] Figure 1 A flowchart of an ecological analysis method for artificial rainfall impact based on regional dynamic matching provided by an embodiment of the present invention; Figure 2A technical roadmap of an ecological analysis method for artificial rainfall enhancement impact based on regional dynamic matching is provided for an embodiment of the present invention; Figure 3 A schematic diagram of a dynamic matching algorithm for an evaluation area according to a specific embodiment of the present invention; Figure 4 A schematic diagram of the spatial distribution of the average single human shadow operation effect of a regional historical regression analysis according to a specific embodiment provided by an embodiment of the present invention; Figure 5 A schematic diagram of the spatial distribution of the Pearson correlation between the rainfall enhancement effect and the NDVI index according to a specific embodiment of the present invention; Figure 6 A schematic diagram of the spatial distribution of the monthly average NDVI residuals of a specific embodiment provided by an embodiment of the present invention; Figure 7 A structural block diagram of an artificial rainfall enhancement impact ecological analysis system based on regional dynamic matching provided by an embodiment of the present invention; Figure 8 It is a schematic diagram of the structure of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0011] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0012] See also Figure 1 , which shows a flow chart of an ecological analysis method of artificial rainfall impact based on regional dynamic matching in the present application.

[0013] like Figure 1 As shown in the figure, the ecological analysis method of artificial rainfall impact based on regional dynamic matching specifically includes the following steps: Step S101, obtaining human shadow operation effect data and meteorological data.

[0014] Step S102, dynamically setting a target sector area and at least one floating comparison sector area according to the meteorological data of the human shadow operation location, and selecting an optimal comparison area in the at least one floating comparison sector area based on the correlation of historical precipitation sequences.

[0015] Step S103, performing non-randomized efficacy analysis and outlier elimination on the target sector area and the comparison area to obtain a rainfall increase effect value, wherein the rainfall increase effect value includes a relative rainfall increase rate and an absolute rainfall increase amount, wherein the non-randomized efficacy analysis is applied to a sequence analysis test, a regional comparison analysis test, a double ratio analysis test, and a regional historical regression analysis test.

[0016] Step S104, calculating the response lag of NDVI to natural precipitation through Pearson correlation, establishing the correlation between the rainfall effect value and NDVI based on the response lag, and separating the independent contribution value of artificial rainfall amount to vegetation change through multiple regression residuals.

[0017] In this embodiment, the rainfall enhancement effect value is mainly reflected in the absolute rainfall enhancement amount and the relative rainfall enhancement rate.

[0018] The absolute rainfall increase is the difference in the time series of the target area, that is, the difference between the rainfall observation value in the target area with artificial rainfall enhancement operations and the precipitation value without artificial rainfall enhancement operations in the historical period; the relative rainfall increase rate is the comparison of the absolute rainfall increase and the precipitation in the target area without artificial rainfall enhancement operations in the historical period.

[0019] The non-randomized efficacy analysis of the target sector area and the comparison area is specifically performed as follows: a sequence analysis test is performed on the target sector area and the comparison area to obtain a first rainfall enhancement effect value, wherein the first rainfall enhancement effect value includes a first relative rainfall enhancement rate and a first rainfall enhancement amount, and the expressions are respectively: , , In the formula, is the first relative rainfall increase rate, is the first absolute rainfall increase, is the precipitation in the target area during the operation period, is the precipitation in the target area during the historical period; A regional comparative analysis test is performed on the target sector area and the comparison area to obtain a second rainfall enhancement effect value, wherein the second rainfall enhancement effect value includes a second relative rainfall enhancement rate and a second rainfall enhancement amount, and the expressions are respectively: , , In the formula, is the second relative rainfall increase rate, is the second absolute rainfall increase, is the precipitation in the comparison area during the operation period; A double ratio analysis test is performed on the target sector area and the comparison area to obtain a third rainfall enhancement effect value, wherein the third rainfall enhancement effect value includes a third relative rainfall enhancement rate and a third rainfall enhancement amount, and the expressions are: , , In the formula, is the third relative rainfall increase rate, The third absolute rainfall increase, is the artificial rainfall rate, is the precipitation in the comparison area during the historical period; A regional historical regression analysis test is performed on the target sector area and the comparison area to obtain a fourth rainfall increase effect value, wherein the fourth rainfall increase effect value includes a fourth relative rainfall increase rate and a fourth rainfall increase amount, and the expressions are respectively: , , In the formula, is the fourth relative rainfall increase rate, It is the fourth absolute rainfall increase. It is the univariate regression relationship between the precipitation in the comparison area and the precipitation in the target area during the historical period.

[0020] After performing non-randomized efficacy analysis on the target sector area and the comparison area to obtain the rainfall enhancement effect value, the method further includes: performing a significance test on the rainfall enhancement effect value. Specifically: A significance test is performed on the first rainfall enhancement effect value and the second rainfall enhancement effect value based on the u test, and the expression is: , , In the formula, is a statistical variable, is the average value of the job sample, is the historical sample average, is the historical sample standard deviation, is the number of job samples, is the final significance test value, is the integration variable; A significance test is performed on the third rainfall enhancement effect value and the fourth rainfall enhancement effect value based on Student's t test, and the expression is: , , In the formula, is the observed rainfall value in the target area - the artificial rainfall increase area, is the expected natural rainfall value in the target area or comparison area without artificial rainfall enhancement, is the number of historical samples, is the strength of the linear relationship between the observed rainfall value and the expected natural rainfall value, is the rainfall value of the target area in the historical period, is the average rainfall value of the target area in the historical period, is the observed rainfall value of the comparison area and artificial rainfall area during the operation period, is the rainfall value of the comparison area in the historical period, is the average rainfall value of the comparison area in the historical period, is the critical value of the t distribution, is the degree of freedom, is the gamma function.

[0021] It should be noted that the arithmetic average of the four test results is intended to get a result closer to the actual situation.

[0022] For non-randomized experiments, the statistical scheme must be determined afterwards, and only the appropriate statistical method can be selected based on the analysis of existing data to evaluate the effect. Efficacy refers to the probability of detecting a certain experimental effect at a certain significance within a certain experimental period. This indicator can guide the selection of experimental units and the selection of statistical schemes. This analysis method uses randomized testing (a type of distribution-free testing method, which has the advantages of not requiring any distribution assumptions and corresponding parameter estimates, and is applicable to small samples and samples from random and non-random sources.) to conduct numerical analysis of the efficacy of non-randomized experiments, and on this basis, select appropriate statistical schemes to conduct an overall evaluation of the effectiveness of artificial rainmaking operations.

[0023] A regression equation with vegetation change (NDVI) as the dependent variable and multiple independent variables including precipitation was established. The precipitation observation value after artificial rainfall enhancement was subtracted from the artificial rainfall enhancement amount to obtain the value without artificial rainfall enhancement. The NDVI value before artificial rainfall enhancement was obtained using the above fitting relationship. Under this fitting equation, the NDVI values ​​after and before artificial rainfall enhancement can be calculated respectively. The subtraction of the two can obtain the quantitative relationship between the impact of artificial rainfall enhancement on vegetation change.

[0024] In summary, the method of the present application obtains the data on the effect of human shadow operations and meteorological data, dynamically sets the target sector area and no less than six floating comparison sector areas in the upwind direction according to the wind data of the -5°C temperature layer at the location of the human shadow operation, and selects the optimal comparison area from no less than six floating comparison sector areas in the upwind direction based on the correlation of historical precipitation sequences, performs non-randomized efficacy analysis and outlier removal on the target sector area and the comparison area, obtains the rainfall effect value, calculates the response lag of NDVI to natural precipitation through Pearson correlation, establishes the correlation between rainfall effect and NDVI based on the response lag, and separates the independent contribution value of artificial rainfall to vegetation change through multivariate regression residuals. The potential patterns of rainfall enhancement effects are identified in complex data, aiming to accurately evaluate the effects of human shadow operations and their ecological responses.

[0025] The method of this application is suitable for the evaluation of operational rainfall enhancement and drought relief operations in the arid areas of Northwest China, especially for long-term and large-scale operations. The method can be widely used in meteorology, ecological environment, agriculture and forestry and other fields to provide decision support for policy formulation and implementation of artificial weather modification operations. Specifically include: Input data: Rainfall enhancement effect part: Human shadow operation record Excel: including operation time, longitude and latitude, etc.; Meteorological element reanalysis products: including vertical pressure layer temperature, wind speed and direction during the operation period of the study area, and total ground precipitation during the operation period and historical period.

[0026] Ecological impact section: Ecological indicator data: such as Normalized Difference Vegetation Change (NDVI) data; Meteorological element data of regression model: such as precipitation, temperature, evapotranspiration, etc.; Geospatial data: study area boundaries.

[0027] Output products: Operation effect evaluation results Excel: Contains the relative rainfall increase rate, absolute rainfall increase, and significance and abnormality test results of four statistical test methods (sequence analysis, regional comparison analysis, double ratio analysis, and regional historical regression analysis) for each operation; Spatial distribution of regional rainfall enhancement effect: The spatial distribution of regional rainfall enhancement effect is obtained by inputting the Excel result of the operation effect evaluation into the interpolation method; Rainfall ecological response map: including Pearson correlation and spatial distribution map of multiple regression residuals.

[0028] This method can provide a test set for testing and improving this method. The data set is: Some shadow work records; ERA5–LAND hourly precipitation data; ERA5 vertical pressure layer data; Normalized Difference Vegetation Change (NDVI) data; Other meteorological element datasets used in regression models; Regional boundaries.

[0029] Main technical indicators: Temporal and spatial resolution: Precipitation reanalysis datasets with local applicability (such as 0.1°x0.1° ERA5–LAND hourly precipitation data) and ecological indicator datasets (such as 250m resolution monthly NDVI index, etc.) can be input; the spatial resolution of the precipitation enhancement effect is interpolated to a grid consistent with the ecological indicators through radial basis. The minimum temporal resolution is monthly.

[0030] Timeliness: Applicable to post-evaluation. When the operation time and location are known, the European Centre for Medium-Range Weather Forecasts (ECMWF) or the Global Forecast System (GFS) short- and medium-range forecast datasets can also be used to predict the rainfall effect. The single evaluation time is within 2 minutes.

[0031] Accuracy: Significance tests such as u test and Student's t test were set, and the interquartile range (IQR) method was set to detect outliers.

[0032] Computational efficiency: The method uses efficient data processing libraries (such as Pandas, NumPy, etc.) to achieve rapid processing of large-scale precipitation and ecological data, and combines multi-threading technology (such as multiprocessing) to improve parallel computing capabilities. In addition, batch processing is performed for each job record, and a custom data caching mechanism is used to reduce repeated calculations and optimize overall execution efficiency.

[0033] Scalability: The method structure is modular and has high scalability. It supports the integration of various meteorological and ecological data and can be flexibly adjusted according to application requirements.

[0034] This method aims to accurately evaluate human shadow operations and their ecological responses (such as vegetation growth) through systematic data processing and statistical tests. The process design covers not only data preprocessing, statistical tests of rainfall enhancement effects and regional dynamic matching, but also post-processing of results and ecological impact analysis. Figure 2 , the overall process can be summarized into the following steps: Step 1: Data reading and preprocessing; Step 2: Non-randomized statistical test of rainfall enhancement effect; Step 2.1: Dynamic matching of evaluation area Step 2.2: Statistical test methods and significance tests Step 2.3: Post-processing of outlier detection Step 3: Spatiotemporal interpolation of rainfall enhancement effect; Step 4: lagged correlation analysis of ecological indicators; Step 5: Multiple regression residual analysis to quantify the contribution of artificial rainfall to ecological indicators; Step 6: Output and visualize the results.

[0035] See also Figure 3 , by extracting the meteorological data of the work site, the target sector area and multiple floating comparison sector areas are dynamically set, and the optimal comparison area is selected based on the correlation of historical precipitation sequences.

[0036] Statistical test methods: including four non-randomized efficacy analyses, namely sequence analysis, regional comparison analysis, double ratio analysis and regional historical regression analysis. The formulas are shown in Table 1: Table 1 Non-randomized statistical test method formula , The significance test of the statistical test method is shown in Table 2: Table 2 Significance test formula , Ecological benefit evaluation: The response lag of NDVI to natural precipitation was calculated by Pearson correlation. The correlation between rainfall enhancement effect and NDVI was established based on the response lag. The independent contribution of artificial rainfall enhancement to vegetation change was separated through multiple regression residuals.

[0037] Application examples: Data sample description: Human shadow operation effect data: operation records in the Hexi Corridor and Qilian Mountains of Gansu recorded by the Human Shadow Office of the Gansu Meteorological Bureau from 2019 to 2022 (samples are shown in Table 3); ERA5–LAND hourly precipitation data of 0.1°x 0.1°; hourly precipitation observation data of regional stations.

[0038] Table 3 Sample of human shadow operation record , Other data: Normalized Difference Vegetation Change (NDVI) at 250-meter resolution over China from 2019 to 2022; Sample rainfall enhancement effect evaluation: Table 3 The sample of human shadow operation record is calculated by the algorithm and the results are shown in Table 4: Table 4 Evaluation results of the sample operation records , Spatial distribution of rainfall enhancement effect: Areas with high total rainfall enhancement values ​​are as follows: Figure 4Points a), b), and c) are distributed in the Suzhulianfeng area in the middle section of the Qilian Mountains, the Shandan Horse Farm area in the eastern section of the Qilian Mountains, the eastern end of the Longshou Mountains, the southwestern Tengger Desert, and the western Wushaoling area from west to east. Most of these areas are located at the junction of mountainous areas and plains. The uplift of the terrain promotes the formation of high-efficiency orographic cloud systems, making them ideal operation areas for artificial rain and snow enhancement.

[0039] Ecological benefit assessment: Figure 5 As can be seen in a) and b) in the figure, the rainfall enhancement effect has a consistent strong and significant correlation in the western part of Longshou Mountain, Shandan Horse Farm and the eastern part of Wushaoling in the southeastern part of the Hexi Corridor (r ≥ 0.456, p < 0.001), indicating that the rainfall enhancement measures here have significantly increased the availability of water and improved the health of vegetation. Multiple regression residual analysis ( Figure 6 ) further revealed that vegetation improvement was mainly concentrated in the middle to eastern sections of the Qilian Mountains, the Heihe main stream basin and the Wushaoling Mountain area. The NDVI residual in the high-altitude mountainous areas reached a growth trend of +0.2 / month, reflecting the significant improvement in vegetation growth and coverage due to artificial rain and snow operations, and the positive impact on high-altitude ecosystems.

[0040] In summary, the application scope of the method of this application is: This method is suitable for the evaluation of operational rainfall enhancement and drought relief operations in the arid areas of Northwest China, especially for long-term and large-scale operations. It can support but is not limited to the following fields: Agriculture and forestry: Assess the role of artificial rainfall in promoting vegetation growth, help formulate reasonable irrigation strategies, and optimize water resource utilization efficiency.

[0041] Ecological and environmental protection: This method has been well applied in high-altitude areas and ecologically sensitive areas (such as the Hexi Corridor), and can be used to monitor and evaluate the positive impacts of artificial rainfall on the ecosystem to guide regional ecological restoration.

[0042] Practical application effect: The results of rainfall enhancement effect evaluation and ecological benefit evaluation of this method in the Hexi Corridor region have high credibility. The areas with high total rainfall enhancement, areas with significant ecological impact and areas with high frequency of artificial rainfall enhancement operations basically coincide with each other.

[0043] Comparison of existing algorithms: Most existing algorithms are based on fixed assessment areas, which makes it difficult to ensure the accuracy of assessment results. There are few studies on ecological benefit assessment, and the data and methods are limited, making it difficult to quantify the impact of rainfall enhancement on NDVI.

[0044] This method developed a dynamic matching algorithm for the evaluation area, which solved the problem that the regional fixity and meteorological interference factors in the traditional evaluation method were difficult to separate. Four non-randomized statistical test methods were used to comprehensively quantify the effect of artificial rainfall enhancement operations. At the same time, an outlier detection mechanism was introduced to improve the reliability of the results. Based on the response lag period, the response of ecological indicators to artificial rainfall enhancement was evaluated and their contributions were separated. An evaluation system for comprehensive artificial rainfall enhancement effects and ecological benefits was constructed. At the same time, pattern recognition and AI anomaly detection based on machine learning were introduced to identify potential patterns of rainfall enhancement effects in complex data. This method aims to accurately evaluate the effects of human shadow operations and their ecological responses (such as vegetation growth).

[0045] See also Figure 7 , which shows a structural block diagram of an artificial rainfall impact ecological analysis system based on regional dynamic matching in the present application.

[0046] like Figure 7 As shown, the ecological response effect analysis system 200 includes an acquisition module 210 , a selection module 220 , an analysis module 230 and an output module 240 .

[0047] Wherein, the acquisition module 210 is configured to acquire the human shadow operation effect data and meteorological data; A selection module 220 is configured to dynamically set a target sector area and at least one floating comparison sector area according to meteorological data of the human shadow operation location, and select an optimal comparison area in the at least one floating comparison sector area based on the correlation of historical precipitation sequences; The analysis module 230 is configured to perform non-randomized efficacy analysis and outlier elimination on the target sector area and the comparison area to obtain a rainfall enhancement effect value, wherein the rainfall enhancement effect value includes a relative rainfall increase rate and an absolute rainfall increase amount, wherein the non-randomized efficacy analysis is applied to a sequence analysis test, a regional comparison analysis test, a double ratio analysis test, and a regional historical regression analysis test; The output module 240 is configured to calculate the response lag of NDVI to natural precipitation through Pearson correlation, establish the correlation between the rainfall effect value and NDVI based on the response lag, and separate the independent contribution value of artificial rainfall amount to vegetation change through multiple regression residuals.

[0048] It should be understood that Figure 7 Modules and references documented in Figure 1 Therefore, the operations and features described above for the method and the corresponding technical effects are also applicable to Figure 7 The modules in it will not be described in detail here.

[0049] In some other embodiments, the embodiments of the present invention further provide a computer-readable storage medium having a computer program stored thereon, and when the program instructions are executed by a processor, the processor is caused to execute the ecological analysis method of artificial rainfall impact based on regional dynamic matching in any of the above method embodiments; As an implementation mode, the computer-readable storage medium of the present invention stores computer-executable instructions, and the computer-executable instructions are configured as follows: Obtain human shadow operation effect data and meteorological data; Dynamically set a target sector area and at least one floating comparison sector area according to meteorological data of the human shadow operation location, and select an optimal comparison area in the at least one floating comparison sector area based on the correlation of historical precipitation sequences; Performing non-randomized efficacy analysis and outlier elimination on the target sector area and the comparison area to obtain a rainfall increase effect value, wherein the rainfall increase effect value includes a relative rainfall increase rate and an absolute rainfall increase amount, wherein the non-randomized efficacy analysis is applied to a sequence analysis test, a regional comparison analysis test, a double ratio analysis test, and a regional historical regression analysis test; The response lag of NDVI to natural precipitation was calculated by Pearson correlation, and the correlation between the rainfall enhancement effect value and NDVI was established based on the response lag. The independent contribution value of artificial rainfall enhancement to vegetation change was separated through multiple regression residuals.

[0050] The computer-readable storage medium may include a program storage area and a data storage area, wherein the program storage area may store an operating system and application programs required for at least one function; the data storage area may store data created based on the use of the artificial rainfall enhancement ecological analysis system based on regional dynamic matching, etc. In addition, the computer-readable storage medium may include a high-speed random access memory, and may also include a memory, such as at least one disk storage device, a flash memory device, or other non-volatile solid-state storage device. In some embodiments, the computer-readable storage medium may optionally include a memory remotely disposed relative to the processor, and these remote memories may be connected to the artificial rainfall enhancement ecological analysis system based on regional dynamic matching via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0051] Figure 8 is a schematic diagram of the structure of an electronic device provided by an embodiment of the present invention, such as Figure 8 As shown, the device includes: a processor 310 and a memory 320. The electronic device may also include: an input device 330 and an output device 340. The processor 310, the memory 320, the input device 330 and the output device 340 may be connected via a bus or other means. Figure 8The example of the connection through the bus is taken. The memory 320 is the above-mentioned computer-readable storage medium. The processor 310 executes various functional applications and data processing of the server by running the non-volatile software programs, instructions and modules stored in the memory 320, that is, the method for analyzing the ecological impact of artificial rainfall based on regional dynamic matching of the above-mentioned method embodiment is realized. The input device 330 can receive input digital or character information, and generate key signal input related to user settings and function controls of the ecological analysis system of artificial rainfall based on regional dynamic matching. The output device 340 may include display devices such as display screens.

[0052] The electronic device can execute the method provided by the embodiment of the present invention, and has the functional modules and beneficial effects corresponding to the execution method. For technical details not described in detail in this embodiment, please refer to the method provided by the embodiment of the present invention.

[0053] As an implementation mode, the electronic device is applied to an artificial rainfall enhancement impact ecological analysis system based on regional dynamic matching, and is used for a client, and includes: at least one processor; and a memory connected to the at least one processor in communication; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can: Obtain human shadow operation effect data and meteorological data; Dynamically set a target sector area and at least one floating comparison sector area according to meteorological data of the human shadow operation location, and select an optimal comparison area in the at least one floating comparison sector area based on the correlation of historical precipitation sequences; Performing non-randomized efficacy analysis and outlier elimination on the target sector area and the comparison area to obtain a rainfall increase effect value, wherein the rainfall increase effect value includes a relative rainfall increase rate and an absolute rainfall increase amount, wherein the non-randomized efficacy analysis is applied to a sequence analysis test, a regional comparison analysis test, a double ratio analysis test, and a regional historical regression analysis test; The response lag of NDVI to natural precipitation was calculated by Pearson correlation, and the correlation between the rainfall enhancement effect value and NDVI was established based on the response lag. The independent contribution value of artificial rainfall enhancement to vegetation change was separated through multiple regression residuals.

[0054] Through the description of the above implementation methods, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solution is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods of each embodiment or some parts of the embodiment.

[0055] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for ecological analysis of artificial rainfall impact based on regional dynamic matching, characterized in that: include: Obtain human shadow operation effect data and meteorological data; Dynamically set a target sector area and at least one floating comparison sector area according to meteorological data of the human shadow operation location, and select an optimal comparison area in the at least one floating comparison sector area based on the correlation of historical precipitation sequences; Performing non-randomized efficacy analysis and outlier elimination on the target sector area and the comparison area to obtain a rainfall increase effect value, wherein the rainfall increase effect value includes a relative rainfall increase rate and an absolute rainfall increase amount, wherein the non-randomized efficacy analysis is applied to a sequence analysis test, a regional comparison analysis test, a double ratio analysis test, and a regional historical regression analysis test; The response lag of NDVI to natural precipitation was calculated by Pearson correlation, and the correlation between the rainfall enhancement effect value and NDVI was established based on the response lag. The independent contribution value of artificial rainfall enhancement to vegetation change was separated through multiple regression residuals.

2. According to claim 1, a method for analyzing the ecological impact of artificial rainfall based on regional dynamic matching is characterized in that: in, The non-randomized efficacy analysis of the target sector area and the comparison area is specifically as follows: A sequence analysis test is performed on the target sector area and the comparison area to obtain a first rainfall enhancement effect value, wherein the first rainfall enhancement effect value includes a first relative rainfall enhancement rate and a first rainfall enhancement amount, and the expressions are respectively: ， ， In the formula, is the first relative rainfall increase rate, is the first absolute rainfall increase, is the precipitation in the target area during the operation period, is the precipitation in the target area during the historical period; A regional comparative analysis test is performed on the target sector area and the comparison area to obtain a second rainfall enhancement effect value, wherein the second rainfall enhancement effect value includes a second relative rainfall enhancement rate and a second rainfall enhancement amount, and the expressions are respectively: ， ， In the formula, is the second relative rainfall increase rate, is the second absolute rainfall increase, is the precipitation in the comparison area during the operation period; A double ratio analysis test is performed on the target sector area and the comparison area to obtain a third rainfall enhancement effect value, wherein the third rainfall enhancement effect value includes a third relative rainfall enhancement rate and a third rainfall enhancement amount, and the expressions are: ， ， In the formula, is the third relative rainfall increase rate, The third absolute rainfall increase, is the artificial rainfall rate, is the precipitation in the comparison area during the historical period; A regional historical regression analysis test is performed on the target sector area and the comparison area to obtain a fourth rainfall increase effect value, wherein the fourth rainfall increase effect value includes a fourth relative rainfall increase rate and a fourth rainfall increase amount, and the expressions are respectively: ， ， In the formula, is the fourth relative rainfall increase rate, It is the fourth absolute rainfall increase. It is the univariate regression relationship between the precipitation in the comparison area and the precipitation in the target area during the historical period.

3. The method for ecological analysis of artificial rainfall impact based on regional dynamic matching according to claim 1 is characterized in that: After performing a non-randomized statistical test on the target sector area and the comparison area to obtain a rainfall enhancement effect value, the method further includes: A significance test is performed on the rainfall enhancement effect value to evaluate the statistical confidence interval of the rainfall enhancement effect of each operation.

4. The method for ecological analysis of artificial rainfall impact based on regional dynamic matching according to claim 3 is characterized in that: The significance test of the rainfall enhancement effect value comprises: A significance test is performed on the first rainfall enhancement effect value and the second rainfall enhancement effect value based on the u test, and the expression is: ， ， In the formula, is a statistical variable, is the average value of the job sample, is the historical sample average, is the historical sample standard deviation, is the number of job samples, is the final significance test value, is the integral variable; A significance test is performed on the third rainfall enhancement effect value and the fourth rainfall enhancement effect value based on Student's t test, and the expression is: ， ， In the formula, is the observed rainfall value in the target area - the artificial rainfall increase area, is the expected natural rainfall value in the target area or comparison area without artificial rainfall enhancement, is the number of historical samples, is the strength of the linear relationship between the observed rainfall value and the expected natural rainfall value, is the rainfall value of the target area in the historical period, is the average rainfall value of the target area in the historical period, is the observed rainfall value of the comparison area and artificial rainfall area during the operation period, is the rainfall value of the comparison area in the historical period, is the average rainfall value of the comparison area in the historical period, is the critical value of the t distribution, is the degree of freedom, is the gamma function.

5. An artificial rainfall impact ecological analysis system based on regional dynamic matching, characterized in that: include: An acquisition module configured to acquire human shadow operation effect data and meteorological data; A selection module configured to dynamically set a target sector area and at least one floating comparison sector area according to meteorological data of a human shadow operation location, and select an optimal comparison area in the at least one floating comparison sector area based on the correlation of a historical precipitation sequence; An analysis module is configured to perform non-randomized efficacy analysis and outlier elimination on the target sector area and the comparison area to obtain a rainfall increase effect value, wherein the rainfall increase effect value includes a relative rainfall increase rate and an absolute rainfall increase amount, wherein the non-randomized efficacy analysis is applied to a sequence analysis test, a regional comparison analysis test, a double ratio analysis test, and a regional historical regression analysis test; The output module is configured to calculate the response lag of NDVI to natural precipitation through Pearson correlation, establish the correlation between the rainfall enhancement effect value and NDVI based on the response lag, and separate the independent contribution value of artificial rainfall to vegetation change through multiple regression residuals.

6. An electronic device, characterized in that: include: At least one processor, and a memory communicatively connected to the at least one processor, wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the method described in any one of claims 1 to 4.

7. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the method according to any one of claims 1 to 4 is implemented.

Images