Artificial directional precipitation vegetation restoration and effect evaluation method

Abstract

The invention belongs to the technical field of vegetation restoration, and provides an artificial directional rainfall enhancement vegetation restoration and effect evaluation method, which comprises the steps of degeneration research area selection, wind gallery construction, rainfall enhancement landscape smoke furnace fixation, comparison area selection, rainfall catalysis, rainfall data acquisition, predicted rainfall calculation, artificial rainfall enhancement effect evaluation and vegetation restoration effect evaluation. Through degeneration research area selection, wind gallery construction, rainfall enhancement landscape smoke furnace fixation and rainfall catalysis, vegetation restoration of a vegetation degeneration area under the directional rainfall enhancement technology is achieved, and the vegetation restoration efficiency is improved; through a stable artificial precipitation enhancement test, comparative analysis of biodiversity indexes and vegetation coverage of a target area and a contrast area is carried out, and accurate evaluation of ecological restoration benefits under artificial directional precipitation enhancement is realized.

Description

Technical Field

[0001] The present invention relates to the technical field of vegetation restoration, and particularly to a method for artificial directional rainfall enhancement for vegetation restoration and effect evaluation. Background Art

[0002] Climate change is another important cause accelerating the degradation of ecosystems and the loss of biodiversity. With the change of global temperature, the actual evaporation loss increases, the runoff depth and water storage decrease relatively, and the impact of climate change on regional hydrology is an important factor in climate impact issues. In the areas where vegetation degradation is caused by climate drought, the primary task is to change the local hydrothermal conditions. While rationally utilizing the existing water resources, new ways to increase water are developed to accelerate the realization of vegetation ecological restoration and achieve the sustainable development of the ecosystem. For the target ecological restoration areas of vegetation degradation, the aerial cloud water resources are developed and utilized, and the artificial directional rainfall enhancement technology is adopted to reduce drought occurrence. Artificial directional rainfall enhancement utilizes the microphysical instability of natural clouds and adopts artificial catalysis methods to change the cloud precipitation physical process, so as to achieve the important purposes of increasing precipitation, alleviating the shortage of water resources in vegetation degradation areas, and accelerating vegetation restoration. At present, artificial rainfall enhancement operations are mainly applied to the agricultural production disaster relief in the dry season of arid areas. The main operation tools include aircraft artificial rainfall enhancement, ground anti-aircraft guns, rockets and other artificial rainfall enhancement and hail prevention operations, as well as landscape smoke furnaces for rainfall enhancement.

[0003] However, in terms of ecological restoration, the research on artificial rainfall enhancement is relatively weak, mainly manifested in: the response relationship between vegetation degradation and rainfall is not clear, lacking a scientific model between targeted artificial rainfall enhancement and vegetation restoration and relevant indicators for artificial rainfall enhancement operations; the operation technical means such as detection and catalysis are backward; lacking long-term stable and scientifically designed artificial rainfall enhancement experiments, and the evaluation of the ecological benefits of vegetation restoration after rainfall enhancement is not strict enough, etc. Summary of the Invention

[0004] In order to overcome the deficiencies of the prior art, the purpose of the present invention is to provide a method for artificial directional rainfall enhancement for vegetation restoration and effect evaluation, so as to achieve more efficient vegetation restoration and more strict evaluation of vegetation restoration effects.

[0005] To achieve the above purpose, the present invention provides the following solutions:

[0006] A method for artificial directional rainfall enhancement for vegetation restoration and effect evaluation includes:

[0007] Calculating the vegetation degradation index of the target research area by using remote sensing inversion NPP and climate NPP, and selecting the areas corresponding to the vegetation degradation index within the preset severely degraded range to obtain the degraded research area;

[0008] Constructing a wind corridor according to the preset site conditions and the high-altitude wind speed and direction during the vegetation growth season, and setting a rainfall enhancement landscape smoke furnace at the upper part of the windward slope corresponding to the upwind direction of the wind corridor in the degraded research area;

[0009] Define a rectangular area based on the ignition length, echo speed, and duration of the rain enhancement landscape smoke furnace, and fix the rain enhancement landscape smoke furnace at the middle position of the short side of the rectangular area;

[0010] Select a comparison area that is a control for the rectangular area on the degraded research area according to the preset control selection requirements;

[0011] When the preset operation conditions are met, ignite AgI smoke sticks through the rain enhancement landscape smoke furnace to obtain the working cloud mass, and use the working cloud mass to catalyze rainfall in the rectangular area;

[0012] Collect the rainfall amounts in the rectangular area and the comparison area before and after catalysis in the rectangular area to obtain rainfall data;

[0013] Use the WRF model to predict the rainfall amount in the rectangular area without catalysis to obtain the predicted rainfall;

[0014] Calculate the absolute and relative effects of artificial rainfall enhancement based on the rainfall data and the predicted rainfall to obtain the evaluation result of the artificial rainfall enhancement effect;

[0015] Calculate and compare the biodiversity index and vegetation coverage in the rectangular area and the comparison area before and after catalysis in the rectangular area to obtain the evaluation result of the vegetation restoration effect.

[0016] Preferably, the expression of the vegetation degradation index is: where VDI is the vegetation degradation index; R P is the climatic NPP; R a is the remotely sensed inversion NPP.

[0017] Preferably, the severe degradation range is 0.6 to 1.

[0018] Preferably, the length of the short side of the rectangular area is the ignition length; the length of the long side of the rectangular area is the product of the echo speed and the duration.

[0019] Preferably, the operation conditions include: weather conditions, guiding air flow direction conditions, echo parameter conditions, cloud top temperature conditions, precipitation intensity conditions, and water vapor pressure conditions; the weather conditions include: frontal precipitation, Mongolian cold vortex, and upper-air northwest airflow.

[0020] Preferably, the expression of the absolute effect is: E = y - y0; where E is the calculated value of the absolute effect; y is the rainfall amount in the rectangular area after catalysis; y0 is the predicted rainfall.

[0021] Preferably, the expression of the biodiversity index is as follows:

[0022] BI = H×0.3 + S×0.25 + C×0.15 + P×0.15 + A×0.15;

[0023] where BI is the calculated value of the biodiversity index; H is the vegetation landscape diversity index; S is the species diversity index; C is the nature reserve index; P is the national protected plant species diversity index; A is the national protected animal species diversity index.

[0024] Preferably, the expression of the vegetation coverage is as follows:

[0025] NDVI = (NIR - R) / (NIR + R);

[0026] where NDVI is the vegetation coverage; NIR is the reflectance of the near-infrared band; R is the reflectance of the red light band.

[0027] Preferably, the expression of the relative effect is: R = (y - y0) / y0 * 100%; where R is the calculated value of the relative effect; y is the precipitation after the rain enhancement operation; y0 is the natural precipitation without the rain enhancement operation.

[0028] The present invention discloses the following technical effects:

[0029] The present invention provides a method for artificial directional rain enhancement vegetation restoration and effect evaluation. By selecting a degraded research area, constructing a wind corridor, fixing a rain enhancement landscape smoke furnace, and conducting rainfall catalysis, the problem of poor vegetation restoration effect in the prior art is solved, and directional rain enhancement restoration of the vegetation degradation area is realized; by conducting rainfall catalysis, calculating predicted rainfall, evaluating the effect of artificial rain enhancement, and evaluating the vegetation restoration effect, the problem of inaccurate evaluation of vegetation restoration in the prior art is solved, and multi-dimensional restoration effect evaluation of rainfall and biodiversity is realized. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for use in the embodiments. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings.

[0031] Figure 1 It is a schematic diagram of the process of artificial directional rain enhancement vegetation restoration and effect evaluation provided by the embodiment of the present invention;

[0032] Figure 2 It is a flowchart of artificial directional rain enhancement vegetation restoration and effect evaluation provided by the embodiment of the present invention. Specific Embodiments

[0033] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0034] The purpose of the present invention is to provide a method for artificial directional rainfall enhancement vegetation restoration and effect evaluation, so as to achieve more efficient vegetation restoration and more rigorous vegetation restoration effect evaluation.

[0035] To make the above objects, features, and advantages of the present invention more obvious and understandable, the present invention will be further described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0036] Figure 1 For the schematic diagram of the artificial directional rainfall enhancement vegetation restoration and effect evaluation process provided by the embodiment of the present invention, as Figure 1 shown, the present invention provides a method for artificial directional rainfall enhancement vegetation restoration and effect evaluation, including:

[0037] Step 100: Calculate the vegetation degradation index of the target research area by using remote sensing inversion of NPP and climatic NPP, and select the areas corresponding to the vegetation degradation index within the preset severely degraded range to obtain the degraded research area;

[0038] Step 200: Construct a wind corridor according to the preset site conditions and the high-altitude wind speed and direction during the vegetation growth season, and set up a rain enhancement landscape smoke furnace on the upper part of the windward slope corresponding to the upwind direction of the wind corridor in the degraded research area;

[0039] Step 300: Define a rectangular area according to the ignition length, echo speed, and duration of the rain enhancement landscape smoke furnace, and fix the rain enhancement landscape smoke furnace at the middle position of the short side of the rectangular area;

[0040] Step 400: Select a comparison area that is in contrast to the rectangular area in the degraded research area according to the preset control selection requirements;

[0041] Step 500: When the preset operation conditions are met, ignite AgI smoke strips through the rain enhancement landscape smoke furnace to obtain the working cloud mass, and use the working cloud mass to catalyze rainfall in the rectangular area;

[0042] Step 600: Collect the rainfall amounts in the rectangular area and the comparison area before and after catalysis in the rectangular area to obtain rainfall data;

[0043] Step 700: Use the WRF model to predict the rainfall amount in the rectangular area without catalysis to obtain the predicted rainfall amount;

[0044] Step 800: Calculate the absolute effect and relative effect of artificial rainfall enhancement based on rainfall data and predicted rainfall amounts to obtain the evaluation result of the artificial rainfall enhancement effect;

[0045] Step 900: Calculate and compare the biodiversity index and vegetation coverage of the rectangular area and the comparison area before and after catalysis to obtain the evaluation result of the vegetation restoration effect.

[0046] Specifically, the expression of the vegetation degradation index is: Among them, VDI is the vegetation degradation index; R P is the climatic NPP; R a is the remotely sensed NPP.

[0047] Preferably, the severe degradation range is from 0.6 to 1.

[0048] Specifically, the short side length of the rectangular area is the ignition length; the long side length of the rectangular area is the product of the echo velocity and the duration.

[0049] Furthermore, the operating conditions include: weather conditions, guiding air flow direction conditions, echo parameter conditions, cloud top temperature conditions, precipitation intensity conditions, and water vapor pressure conditions; the weather conditions include: frontal precipitation, Mongolian cold vortex, and upper air northwest air flow.

[0050] Specifically, the expression of the absolute effect is: E = y - y0; where E is the calculated value of the absolute effect; y is the rainfall amount in the rectangular area after catalysis; y0 is the predicted rainfall amount.

[0051] Preferably, the expression of the biodiversity index is:

[0052] BI = H×0.3 + S×0.25 + C×0.15 + P×0.15 + A×0.15;

[0053] Among them, BI is the calculated value of the biodiversity index; H is the vegetation landscape diversity index; S is the species diversity index; C is the nature reserve index; P is the national protected plant species diversity index; A is the national protected animal species diversity index.

[0054] Specifically, the expression of the vegetation coverage is:

[0055] NDVI = (NIR - R) / (NIR + R);

[0056] Among them, NDVI is the vegetation coverage; NIR is the reflectance of the near-infrared band; R is the reflectance of the red light band.

[0057] Further, the expression for the relative effect is: R = (y - y0) / y0 * 100%; where R is the calculated value of the relative effect; y is the precipitation after the rain enhancement operation; and y0 is the natural precipitation without the rain enhancement operation.

[0058] Reference Figure 2 , the vegetation restoration process and evaluation process of this embodiment are described as follows:

[0059] 1) Diagnose the vegetation degradation, and select the severely degraded areas as the target areas for the artificial directional rain enhancement vegetation restoration technology;

[0060] 2) According to the site conditions, construct a wind corridor according to the wind speed and direction at high altitude during the vegetation growth season, select the area with higher terrain on the upwind side of the wind corridor located in the vegetation degradation area, and place landscape smoke furnaces;

[0061] 3) Determine the influence range according to the ignition length, echo speed and duration of the landscape smoke furnace, and proofread the long side of the rectangle; the short side length of the rectangle is the length of the particulate matter dispersed after the landscape smoke furnace is ignited, and the long side of the rectangle is determined by multiplying the radar detection echo moving speed by the catalytic action time. In the determined target rectangular area, grids are delimited according to 1KM * 1KM, and automatic rain gauges are placed.

[0062] 4) Without being affected by the artificial catalysis operation, according to the statistically prevailing wind direction at high altitude in the test, select a comparison area on the upwind side or the side perpendicular to the wind direction of the artificial catalysis operation. The terrain and area of the comparison area are similar to those of the target area, and the weather systems and precipitation types affected by the two areas during the operation period and non-operation period are similar. Grids are delimited according to 1KM * 1KM in the comparison area, and automatic rain gauges are placed.

[0063] 5) Precipitation forecast and evaluation of the impact of landscape smoke furnaces on precipitation. Use the WRF model, simulate precipitation using historical meteorological data and perform regression analysis with the actual rainfall data to find the precipitation forecast correction coefficient; at the same time, combine the two sets of collected data, one set is the precipitation observation and precipitation forecast during the operation period of the landscape smoke furnace; the other set is the precipitation observation and precipitation forecast during the non-operation period of the landscape smoke furnace, and estimate the impact of the operation period of the landscape smoke furnace on precipitation through the comparison between these two sets of data and the comparison of data between the target area and the comparison area.

[0064] 6) Based on the natural geographical background characteristics of the artificial rain enhancement area, obtain the characteristic data of the artificial rain enhancement effect from remote sensing information sources, artificial rain enhancement operation data, ground meteorological and vegetation observation data, determine the evaluation factors to form the criterion layer, and then select evaluation indicators according to each evaluation factor to form the index layer; construct an artificial rain enhancement effect index model; assign weights to the indicators respectively and substitute them into the index model to evaluate the artificial rain enhancement effect.

[0065] Further, the method for determining the target area:

[0066] 1) Select the areas with severe vegetation degradation according to the vegetation degradation level (refer to Table 1); these areas will be used as the target areas.

[0067] Use remotely sensed NPP to represent the actual productivity and the NPP calculated by the climate model to represent the potential productivity, and establish the Vegetation Degradation Index (VDI) based on the relationship between the two. Its value ranges from 0 to 1.

[0068] Table 1

[0069]

[0070] 2) According to the site conditions, construct a wind corridor based on the high-altitude wind speed and direction during the vegetation growing season, select the upwind direction of the wind corridor located in the vegetation degradation area, and install an artificial rainfall enhancement landscape smoke furnace on the upper part of the windward slope of the mountain.

[0071] 3) Define a rectangular area based on 1) and 2). The artificial rainfall enhancement landscape smoke furnace is located in the middle of the short side of the rectangular area. Determine the influence range according to the ignition length, echo speed, and duration of the smoke furnace, and calibrate the long side of the rectangle; the short side length of the rectangle is the length of the particulate matter dispersed after the ignition of the landscape smoke furnace, and the long side of the rectangle is determined by multiplying the moving speed of the radar detection echo by the catalytic action time.

[0072] Optionally, the selection of the comparison area usually needs to meet the following requirements:

[0073] 1) Not affected by artificial catalysis operations. According to the prevailing high-altitude wind direction of the statistics of the experiment, the comparison area should be selected in the upwind direction or the side perpendicular to the wind direction of the artificial catalysis operation.

[0074] 2) The terrain, area are similar to the target area to eliminate the differences in precipitation caused by the terrain.

[0075] 3) The set area of the comparison area is the same as that of the target area.

[0076] 4) Both areas should have relatively dense precipitation observation points (the design interval is 1000 meters).

[0077] Preferably, it is based on the WRF model atmospheric precipitation prediction technical method. The Weather Research and Forecast (WRF) model is a new generation of mesoscale numerical weather prediction model jointly developed by the meteorological community, and has broad application prospects in weather forecasting, atmospheric chemistry, and regional climate. The model used in this embodiment adopts the Arakawa-C coordinate in the horizontal direction and the shape-following coordinate (referred to as the mass coordinate) in the vertical direction. It uses a 3rd-order accurate Runge-Kutta time integration scheme with a time step of 90 s. In the vertical direction, it adopts the η coordinate and is divided into 27 layers, with the top layer pressure of 50 hPa. The model simulation adopts double nesting. The center point of the simulation area is located at the center of the vegetation degradation area. The horizontal grid distances of the coarse and fine grids are 27 km and 9 km respectively, and the corresponding grid points are 128x96 and 130x910 respectively. The initial background field uses 1°*1° NCEP global reanalysis data, and the boundary is changed every 6 hours. The integration time is 24 hours, the time step is 90 s, and the simulation results are output every hour. Considering that this embodiment mainly simulates the precipitation process, the microphysical scheme and cumulus convection parameterization scheme that have a greater impact on precipitation are selected for analysis. In order to better compare and analyze the influence of precipitation schemes on the simulation results, the other physical process schemes are completely the same, which are: the RRTM long-wave radiation scheme, the Dudhia short-wave radiation scheme, the Noah and Surface model surface process scheme, the YSU boundary layer parameterization scheme, and the Monin-Obukhov surface layer scheme. Data source: The topographic data used is from the WRF official website (http: / / www.Wrfmodel.org); the measured precipitation data used is from the conventional observation data of a certain country's meteorological bureau, and this data is used as the true value for evaluating the model-simulated precipitation.

[0078] Furthermore, the artificial directional rainfall enhancement technical method: The artificial directional rainfall enhancement technology mainly uses ground-based AgI smoke furnaces to burn AgI smoke sticks, and relies on the updraft to bring the artificial ice nuclei AgI into the cloud to be catalyzed for spreading, affecting the microphysical process of the cloud to achieve the purpose of artificial rainfall enhancement. Understanding and mastering the correct catalytic conditions and methods are the keys to artificial rainfall enhancement. The artificial rainfall enhancement monitoring and identification technology. Artificial rainfall enhancement must be catalyzed at the appropriate part and at the appropriate time of the cloud to be effective. For example, natural precipitation in precipitation-stratiform clouds generally develops relatively fully, and the existence of supercooled water is often regarded as a sign suitable for artificial rainfall enhancement catalytic operations, and they only exist in a certain part and a certain period of the cloud. Therefore, real-time monitoring of different cloud systems, obtaining multiple pieces of information reflecting the operation condition criteria, and real-time identifying and grasping the favorable operation timing and location are one of the key technologies to reduce missed operations and improve the effect of artificial rainfall enhancement.

[0079] Preferably, the operation condition selection:

[0080] 1) Weather conditions. There are three types of operating weather conditions: frontal precipitation, Mongolian cold vortex, and upper-air northwest airflow.

[0081] 2) Direction of the guiding airflow. The wind direction at 500 hPa in the upper air is the guiding wind direction for the operating cloud. In this embodiment, it is stipulated that when the wind direction at 500 hPa is the wind direction required during the vegetation restoration period, it is suitable for operation.

[0082] 3) Echo parameters of the operating cloud. The echo parameters of the operating cloud are provided by the Doppler radar of the meteorological bureau in the study area. It is stipulated that when the echo reaches 35 dBz and the echo top height is greater than 7 km, it is suitable for igniting the landscape smoke furnace.

[0083] 4) Specific determination indicators are: the cloud top temperature ranges from -25 °C to -5 °C, the cloud system has a precipitation intensity greater than 0.1 mm / h, and the atmospheric water vapor pressure in the seeding area is greater than the ice surface saturation water vapor pressure. These three points are essential indicators for the potential conditions of the rain enhancement operation.

[0084] Optionally, the catalysis time and dosage are determined as follows: Each AgI smoke furnace can hold 20 AgI smoke sticks at the same time. Each smoke stick is 0.8 m long, with an AgI content of 100 g and can burn for 20 minutes. The control module of the AgI smoke furnace can be determined according to factors such as the size, strength, and moving speed of the cloud mass being operated. Using the radar echo in the radar map, the radar echo shows the moving direction and speed of the system to determine the operation time of the landscape smoke furnace. At the same time, one or more smoke sticks can also be ignited, or multiple smoke sticks can be ignited at different times.

[0085] Preferably, in this embodiment, the restoration effect of the technology on the vegetation is evaluated by assessing the changes in rainfall and plant growth before and after the artificial rain enhancement technology within a growing season.

[0086] Furthermore, the quantitative evaluation of the artificial rain enhancement effect usually adopts a statistical method based on regional historical regression. Its basic idea is to select appropriate target areas and control areas, fit the rainfall correlation between the two areas according to the historical data of the two areas, and then calculate the rainfall estimated value of the target area from the rainfall in the control area during the operation period. By comparing it with the actual rainfall in the target area, the increased precipitation due to artificial rain enhancement can be obtained.

[0087] 1) The statistical analysis method uses precipitation as the statistical variable to determine whether the precipitation in the operation area increases before and after rain enhancement. The operation period and non-operation period should be separated. The operation target area is designed to install an automatic rain gauge per square kilometer. During the operation area and non-operation period, the ground rainfall in the target area and the comparison area is actually collected.

[0088] 2) The numerical simulation method is a mathematical model gradually established based on the cloud-precipitation formation theory. By predicting the precipitation of natural clouds and then comparing it with the measured value of the precipitation after artificial operation, the rain enhancement effect can be determined. The rainfall distribution predicted by the WRF model is used.

[0089] 3) The regression method is to consider the weather system of precipitation enhancement operations, the spatio-temporal distribution of precipitation enhancement operations, the aging effect of catalyst diffusion and catalysis, the spatio-temporal fluctuations of natural precipitation, etc. during statistical tests. Finally, a correlation analysis method between the operation target area and the comparison area is established, and the rainfall amounts in the two areas under historically similar weather conditions are analyzed to construct correction parameters for more detailed evaluation of the effect of artificial precipitation enhancement.

[0090] Specifically, the operation unit is specified as the 24-hour precipitation amount, that is, the daily rainfall amount is used as the statistical variable. Let y be the precipitation amount after the precipitation enhancement operation, and y0 be the natural precipitation amount without the precipitation enhancement operation. Then the effect of the artificial precipitation enhancement can be expressed as:

[0091] E = y - y0

[0092] R = (y - y0) / y0 * 100%

[0093] Thus, three situations occur. When y > y0, it indicates a positive effect; when y < y0, it indicates a negative effect; when y = y0, it indicates no effect. Since the two quantities y and y0 cannot be measured simultaneously. After the precipitation enhancement operation, only y can be measured, while y0 cannot be measured; conversely, y0 can be measured, while y cannot be measured. The method for estimating y0 adopts numerical simulation methods and regression analysis methods to make a timed, located, and quantitative forecast for a precipitation process to meet the accuracy of effect inspection. At the same time, the regional comparison method is adopted to separately count the rainfall amounts in the comparison area and the target area, and then compare the rainfall amounts in the comparison area and the target area. Finally, the effect and benefit of the artificial precipitation enhancement operation are calculated.

[0094] Furthermore, the method for evaluating the vegetation restoration effect. Two indicators, the biodiversity index and the vegetation coverage, are selected to compare and analyze the changes in the indicator values between the target area and the comparison area to analyze the restoration effect.

[0095] Specifically, the biodiversity index. It is the weighted sum of five evaluation indicators, namely the vegetation landscape diversity index, the species diversity index based on ecosystem types, the nature reserve index, the national protected plant species diversity index, and the national protected animal species diversity index. The weights of each evaluation indicator and the establishment of the weights of the sub-indicators involved in calculating a certain index are determined by the expert consultation method. This guide recommends the following weight settings:

[0096] Biodiversity index (BI) = Vegetation landscape diversity index (H) × 0.3 + Species diversity index (S) × 0.25 + Nature reserve index (C) × 0.15 + National protected plant species diversity index (P) × 0.15 + National protected animal species diversity index (A) × 0.15;

[0097] 1) Vegetation landscape diversity index (H)

[0098] Adopt the calculation expression of the Shannon - Wiener diversity index, that is:

[0099]

[0100] In the formula, H is the Shannon - Wiener diversity index of the vegetation landscape in the region, P i is the proportion of the area occupied by the vegetation landscape type (vegetation formation) i in this region, and n is the number of vegetation formations. The larger the value of H, the greater the vegetation landscape diversity and the richer the ecosystem.

[0101] 2) Species diversity index (S)

[0102] Species diversity index (S)= SI coniferous forest × 0.08 + SI coniferous - broad - leaved mixed forest × 0.2 + SI broad - leaved forest × 0.4 + SI bamboo forest × 0.05 + SI shrubbery × 0.05 + SI grassland × 0.03 + SI meadow × 0.03 + SI sparse vegetation × 0.02 + SI wetland × 0.1 + SI desert ecosystem × 0.01 + SI agricultural ecosystem × 0.03;

[0103] 3) Nature reserve index (C)

[0104] Based on the area of various types and levels of nature reserves and the area of wildlife - type nature reserves in the region after normalization processing, calculate the nature reserve index:

[0105] Nature reserve index (C)= CI national - level nature reserve × 0.6 + CI provincial - level nature reserve × 0.3 + CI city - county - level nature reserve × 0.1;

[0106] 4) National protected plant diversity index (P)

[0107] Count the types and quantities of national protected plants in the region. After quantity normalization processing, calculate the national protected plant and animal species diversity indices:

[0108] National protected plant species diversity index (P)= PI national first - class protected plants × 0.65 + PI national second - class protected plants × 0.35;

[0109] 5) National protected animal species diversity index (A)

[0110] Count the types and quantities of national protected animals in the region. After quantity normalization processing, calculate the national protected plant and animal species diversity indices:

[0111] National protected animal species diversity index (A)= AI national first - class protected animals × 0.65 + AI national second - class protected animals × 0.35;

[0112] Optionally, data sources: the number and proportion of area of regional vegetation formations: obtained based on the business statistics of local forestry (forest inventory), environmental protection (ecological protection), and agriculture-related departments, and supplemented by on-site investigations combined with the interpretation of remote sensing images. The area of various ecosystem types in the region: obtained based on the business statistics of local land and resources (land use data), forestry (forest stand survey), environmental protection, and agriculture-related departments, and supplemented by on-site investigations combined with the interpretation of remote sensing images. The area of various types of protected areas in the region: provided by the superior competent department of the corresponding type of protected area. The types and quantities of national key protected plants and animals in the region: sourced from the list of national key protected wild animals and plants provided by the local forestry department.

[0113] Furthermore, vegetation coverage. The vegetation coverage is adopted. The normalized difference vegetation index NDVI is the most commonly used vegetation index. Therefore, this paper selects this index to establish an estimation model for vegetation coverage. The NDVI calculation formula is as follows:

[0114] NDVI = (NIR - R) / (NIR + R)

[0115] Preferably, the rain-enhancing landscape smoke furnace: The rain-enhancing landscape smoke furnace consists of a smoke pipe, a smoke furnace, an ignition control system, and a power supply system. By setting the ignition time and number of the smoke pipe, the smoke pipe can be ignited normally at the selected time, burning the catalyst, releasing the catalytic flame agent into the air through the smoke furnace, and being lifted into the cloud under the action of the updraft to achieve the effect of rain (snow) enhancement.

[0116] Preferably, the technical implementation principles:

[0117] 1) Targeted principle: The artificial directional rain enhancement technology targets the vegetation degradation areas, combines the water demand for local vegetation degradation, the spatio-temporal distribution characteristics of cloud water resources, and the artificial rain enhancement potential, etc., selects the areas of vegetation degradation test areas that are conducive to artificial rain enhancement, and carries out regional vegetation restoration in a targeted manner.

[0118] 2) Comparative principle: In view of the site conditions and cloud water resources of the vegetation restoration target area, reasonably set the positions of the landscape smoke furnaces, and reasonably delimit the comparison areas based on radar, wind speed, wind direction, etc., so that they are not affected by artificial rain enhancement catalysis and can be compared with the rainfall in the target area to provide scientific and effective data for the benefit evaluation of artificial directional rain enhancement vegetation restoration.

[0119] 3) Principle of operability: Fully consider the cloud water resources in the area where the artificial directional rainfall enhancement vegetation restoration technology is implemented, reasonably formulate the field monitoring plan of automatic weather stations or automatic rain gauges in the target area and the comparison area, and on this basis, formulate an evaluation index system for the vegetation restoration effect under the artificial rainfall enhancement technology that is easy to operate. The selection of evaluation indicators and their parameters fully considers the quantification, measurability, and availability of data, and the evaluation method has strong operability in application.

[0120] 4) Principle of demonstration: Vegetation restoration based on artificial measures is a long-term and arduous task. The artificial directional rainfall enhancement vegetation restoration technology based on ecology and meteorology can accelerate the vegetation restoration process and improve the restoration efficiency. Therefore, the fundamental purpose of this embodiment guide is to long-term monitor the implementation effect of this technology in the field test site, continuously adjust the implementation plan through the results, make it scientific and operable, and be able to be demonstrated, promoted, and applied.

[0121] The beneficial effects of the present invention are as follows:

[0122] The present invention realizes the directional rainfall enhancement restoration of the vegetation degradation area and improves the vegetation restoration efficiency through the selection of the degradation research area, the construction of the wind corridor, the fixation of the rainfall enhancement landscape smoke furnace, and rainfall catalysis; through rainfall catalysis, predicted rainfall calculation, evaluation of the artificial rainfall enhancement effect, and evaluation of the vegetation restoration effect, it provides a long-term and stable rainfall enhancement experiment and realizes the accurate evaluation of the ecological benefit restoration by artificial directional rainfall enhancement.

[0123] Each embodiment in this specification is described in a progressive manner. The key point of each embodiment is to illustrate the differences from other embodiments. For the same and similar parts among the embodiments, reference can be made to each other.

[0124] Specific examples are used in this article to elaborate on the principle and implementation manner of the present invention. The description of the above embodiments is only used to help understand the method and its core idea of the present invention; at the same time, for those of ordinary skill in the art, based on the idea of the present invention, there will be changes in the specific implementation manner and application scope. In summary, the content of this specification should not be construed as a limitation to the present invention.

Claims

1. An artificial directional rainfall enhancement vegetation restoration and effect evaluation method, characterized in that Including: Calculating the vegetation degradation index of the target research area by using remote sensing inversion of NPP and climatic NPP, and selecting the area corresponding to the vegetation degradation index within the preset severe degradation range to obtain the degradation research area; Constructing a wind corridor according to the preset site conditions and the high-altitude wind speed and direction during the vegetation growth season, and setting up an artificial rainfall enhancement landscape smoke furnace at the upper part of the windward slope corresponding to the upwind direction of the wind corridor in the degradation research area; Defining a rectangular area according to the ignition length, echo speed and duration of the artificial rainfall enhancement landscape smoke furnace, and fixing the artificial rainfall enhancement landscape smoke furnace at the middle position of the short side of the rectangular area; Selecting a comparison area that is in contrast to the rectangular area in the degradation research area according to the preset comparison selection requirements; When the preset operation conditions are met, firing AgI smoke sticks through the artificial rainfall enhancement landscape smoke furnace to obtain the operation cloud mass, and using the operation cloud mass to catalyze rainfall in the rectangular area; Collecting the rainfall amounts in the rectangular area and the comparison area before and after catalysis in the rectangular area to obtain rainfall data; Predicting the rainfall amount in the rectangular area without catalysis by using the WRF model to obtain the predicted rainfall amount; Calculating the absolute effect and relative effect of artificial rainfall enhancement according to the rainfall data and the predicted rainfall amount to obtain the evaluation result of the artificial rainfall enhancement effect; Calculating and comparing the biodiversity index and vegetation coverage in the rectangular area and the comparison area before and after catalysis in the rectangular area to obtain the evaluation result of the vegetation restoration effect.

2. The artificial directional rainfall enhancement vegetation restoration and effect evaluation method according to claim 1, characterized in that The expression of the vegetation degradation index is as follows: where VDI is the vegetation degradation index; R P is the climate NPP; R a is the remotely sensed NPP inversion.

3. The artificial directional rainfall enhancement vegetation restoration and effect evaluation method according to claim 1, characterized in that The severe degradation range is from 0.6 to 1.

4. The artificial directional rainfall enhancement vegetation restoration and effect evaluation method according to claim 1, wherein, The length of the short side of the rectangular area is the ignition length; the length of the long side of the rectangular area is the product of the echo speed and the duration.

5. A method for artificial directional rainfall enhancement vegetation restoration and effect evaluation according to claim 1, characterized in that, The operation conditions include: weather conditions, guiding air flow direction conditions, echo parameter conditions, cloud top temperature conditions, precipitation intensity conditions and water vapor pressure conditions; the weather conditions include: frontal precipitation, Mongolian cold vortex and upper-air northwest air current.

6. The artificial directional rainfall enhancement vegetation restoration and effect evaluation method according to claim 1, characterized in that The expression of the absolute effect is: E = y - y0; where, E is the calculated value of the absolute effect; y is the rainfall amount in the rectangular area after catalysis; y0 is the predicted rainfall amount.

7. An artificial directional rainfall enhancement vegetation restoration and effect evaluation method according to claim 1, characterized in that The expression of the biodiversity index is: BI = H×0.3 + S×0.25 + C×0.15 + P×0.15 + A×0.15; where, BI is the calculated value of the biodiversity index; H is the vegetation landscape diversity index; S is the species diversity index; C is the nature reserve index; P is the national protected plant species diversity index; A is the national protected animal species diversity index.

8. The method for artificial directional rainfall enhancement vegetation restoration and effect evaluation according to claim 1, characterized in that, The expression of the vegetation coverage is: NDVI = (NIR - R) / (NIR + R); where, NDVI is the vegetation coverage; NIR is the reflectance in the near-infrared band; R is the reflectance in the red light band.

9. The artificial directional rainfall enhancement vegetation restoration and effect evaluation method according to claim 6, characterized in that The expression of the relative effect is: R = (y - y0) / y0 * 100%; where, R is the calculated value of the relative effect; y is the precipitation amount after the rainfall enhancement operation; y0 is the natural precipitation amount without the rainfall enhancement operation.

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