A method for predicting and applying ecological water shortage of vegetation in a mining area

Abstract

The application discloses a kind of mine area vegetation ecological water shortage quantity prediction and application method, it is related to the field of water conservation coal mining in mine area, including: obtaining mine area data, and based on satellite remote sensing obtains mine area index data in different time periods;Based on spatial data management tool, obtain each index thematic layer;Definition mine area vegetation ecological water shortage quantity, in mining area of mine area, calculate the vegetation ecological water requirement of this area before and after mining, clear the vegetation ecological water shortage quantity distribution of mining area;Extract index data, based on neural network prediction mine area unmined area vegetation ecological water shortage quantity;Application vegetation ecological water shortage quantity distribution law, divide mine area unmined area water resource protection grade.The present application can accurately predict the vegetation ecological water shortage quantity of mine area after large-scale coal mining activities, and divide the water resource protection grade of mine area, which provides an important theoretical basis for the coordinated development of ecological fragile zone mine area well coal resource development and water resource protection.

Description

Technical Field

[0001] This invention relates to the field of water-conserving coal mining in mining areas, and in particular to a method for predicting and applying ecological water shortage in mining areas. Background Technology

[0002] Current research on water resource protection in mining areas mainly focuses on the impact of coal seam mining on groundwater resources and surface ecology, while research on water resource and ecological geological environment protection in ecologically fragile mining areas from the perspective of vegetation ecology's water needs (or shortages) is relatively rare.

[0003] CN110727900A discloses a remote sensing early warning and water shortage estimation method for watershed vegetation drought, including: spatial data processing and information extraction, extracting multi-scale watershed information, vegetation type information, runoff information, precipitation information, and soil moisture information; drought stress early warning, calculating changes in water resources and concurrent vegetation changes, and issuing drought early warning based on the instantaneous evapotranspiration index; and estimating vegetation drought water shortage, estimating water shortage for a specific monitoring period based on historical multi-year average water consumption within a specific time period and water consumption within a specific time period of the monitoring year. While this scheme addresses the problem of watershed drought early warning from the perspective of vegetation drought water shortage, the characteristics of the timeliness before and after mining disturbances, as well as the vegetation water shortage status and definition before and after disturbances, are significantly different from those in the watershed area. Therefore, this scheme is clearly unsuitable for predicting vegetation ecological water shortages in mining areas and for classifying water resource protection levels in mining areas. Summary of the Invention

[0004] To address the shortcomings of existing technologies, the purpose of this invention is to provide a method for predicting and applying ecological water shortage in mining areas. This method can accurately predict ecological water shortage in mining areas after large-scale coal mining activities and classify the water resource protection level of mining areas, providing an important theoretical basis for the coordinated development of underground coal resource development and water resource protection in ecologically fragile mining areas.

[0005] To achieve the above objectives, the present invention is implemented through the following technical solution:

[0006] Embodiments of the present invention provide a method for predicting and applying ecological water shortage in mining areas, including:

[0007] Acquire mining area data and obtain mining area indicator data for different time periods based on satellite remote sensing;

[0008] Based on spatial data management tools, obtain thematic layers for each indicator;

[0009] Define the ecological water deficit of vegetation in the mining area, calculate the ecological water demand of vegetation in the mining area before and after mining, and clarify the distribution of ecological water deficit of vegetation in the mining area.

[0010] Extract indicator data and predict the ecological water shortage of vegetation in unexploited areas of the mining area based on neural networks;

[0011] Based on the distribution patterns of water shortage in vegetation ecosystems, the water resource protection levels of unexploited areas in mining districts are classified.

[0012] As a further implementation method, based on ArcGIS spatial analysis functions and the boundary range of the mining area, a raster thematic map is drawn, showing the land cover type in the mining area during the pre-mining and post-mining periods, and the land cover type in the unmined area during the pre-mining period.

[0013] As a further implementation method, the ecological water shortage of vegetation in the mining area is the difference between the ecological water demand of vegetation in the area before mining and the ecological water demand of vegetation in the area after large-scale mining activities.

[0014] As a further implementation method, the vegetation ecological water demand in the mining area before and after mining and in the unmined area before mining are calculated based on the area quota method.

[0015] To analyze the distribution of vegetation ecological water demand in the mining area during the pre-mining and post-mining periods, a differential analysis was performed on the thematic layer in ArcGIS to obtain a thematic map of vegetation ecological water shortage distribution in the mining area.

[0016] As a further implementation, the area quota method calculation formula is as follows:

[0017] W = ∑W i =∑A i ri

[0018] In the formula, W is the total ecological water requirement of vegetation, in m³. 3 Wi represents the total ecological water requirement for vegetation type i, in m³. 3 Ai is the area of ​​vegetation type i, in meters. 2 ri is the ecological water requirement quota for vegetation type i, in m³. 3 / m 2 ;

[0019] As a further implementation method, the prediction process for vegetation ecological water shortage in the unexploited areas of the mining area is as follows:

[0020] Divide the mining area into basic unit grids;

[0021] By using basic unit grids, data on corresponding indicators of basic unit grids in the thematic maps of ecological water shortage, coal seam thickness, and drought index in the mining area are extracted respectively.

[0022] Using the drought index and coal seam thickness of the mining area as input factors and vegetation ecological water shortage as output factors, a vegetation ecological water shortage prediction model is established based on the RBF neural network.

[0023] Based on the prediction model and combined with the index data of the basic unit grid in the unmined area of ​​the mining area, thematic maps and distribution patterns of ecological water shortage after coal mining activities in the unmined area are predicted.

[0024] As a further implementation, the coefficient of determination is selected as the evaluation index of the prediction model, and the formula for calculating the coefficient of determination is:

[0025]

[0026] In the formula, SSR is the regression sum of squares, and SST is the total sum of squares.

[0027] As a further implementation method, the water resource protection level of mining areas is classified according to the degree of water shortage in unexploited areas.

[0028] As a further implementation method, the mining area data includes geological survey data, mining status data, and meteorological data.

[0029] As a further implementation method, for the mining area, a pre-mining time period and a post-mining time period are selected for that area; for the unmined area, the post-mining time period of the mining area is used as the pre-mining time period of the unmined area.

[0030] The beneficial effects of this invention are as follows:

[0031] This invention acquires mining area data and, based on satellite remote sensing, obtains mining area indicator data for different time periods; it also uses spatial data management tools to obtain thematic layers for each indicator; furthermore, it defines the ecological water shortage of vegetation in the mining area; within the mining area, it calculates the ecological water demand of vegetation before and after mining, clarifying the distribution of ecological water shortage in the mining area; it extracts indicator data from the mining area and predicts the ecological water shortage of vegetation in the unmined areas of the mining area based on neural networks; and it applies the distribution law of ecological water shortage of vegetation to classify the water resource protection level of the unmined areas of the mining area. This method can effectively play a role in the protection of water resources and the planning of mining areas, has wide applicability, and provides an important theoretical basis for the coordinated development of underground coal resource development and water resource protection in ecologically fragile mining areas. Attached Figure Description

[0032] The accompanying drawings, which form part of this invention, are used to provide a further understanding of the invention. The illustrative embodiments of the invention and their descriptions are used to explain the invention and do not constitute an improper limitation of the invention.

[0033] Figure 1 This is a flowchart of the present invention according to one or more embodiments;

[0034] Figure 2 This is a map showing the distribution of water resource protection levels in unexploited areas of a certain mining district. Detailed Implementation

[0035] Example 1:

[0036] This embodiment provides a method for predicting and applying ecological water shortage in mining areas, such as... Figure 1 As shown, it includes:

[0037] Acquire mining area data and obtain mining area indicator data for different time periods based on satellite remote sensing;

[0038] Based on spatial data management tools, obtain thematic layers for each indicator;

[0039] Define the ecological water deficit of vegetation in the mining area, calculate the ecological water demand of vegetation in the mining area before and after mining, and clarify the distribution of ecological water deficit of vegetation in the mining area.

[0040] Extract indicator data and predict the ecological water shortage of vegetation in unexploited areas of the mining area based on neural networks;

[0041] Based on the distribution patterns of water shortage in vegetation ecosystems, the water resource protection levels of unexploited areas in mining districts are classified.

[0042] Specifically, S1. Collect data on the mining area, mainly including data on geological surveys, mining conditions, and meteorological data.

[0043] Furthermore, the mining area data includes: clearly defining the boundary between the mined and unmined areas in the mining area, the corresponding time before and after mining of coal seams in the mined area, the thickness of coal seams in the entire mining area, rainfall, evaporation, drought index and other indicators; among which, the drought index refers to the ratio of annual average evaporation to rainfall.

[0044] S2. Based on satellite remote sensing, acquire data on indicators such as land cover type in mining areas at different time periods.

[0045] Furthermore, the different time periods specifically refer to: for mining areas, a certain year before mining and a certain year after mining are selected; for unmined areas, a certain year after mining in the mining area is often used as the pre-mining period for the unmined area.

[0046] S3. Based on ArcGIS spatial data management tools, obtain thematic layers for each indicator.

[0047] Furthermore, based on ArcGIS spatial analysis functions and the boundary range of the mining area, raster thematic maps of coal seam thickness, drought index, etc., were drawn for the entire mining area, and the land cover types (divided into forest, grassland and farmland, etc.) were drawn for the pre-mining and post-mining periods in the mining area, and the land cover type thematic map of the unmined area was drawn for the pre-mining period.

[0048] S4. Define the ecological water shortage of vegetation in the mining area.

[0049] Furthermore, the ecological water shortage of vegetation in mining areas is defined as the difference between the ecological water demand of vegetation in the area before mining and the ecological water demand of vegetation in the area after large-scale mining activities.

[0050] S5. In the mining area, calculate the ecological water demand of vegetation before and after mining, and clarify the distribution of ecological water shortage of vegetation in the mining area.

[0051] Furthermore, the specific steps are as follows:

[0052] S51. Calculate the vegetation ecological water requirement in the pre-mining and post-mining periods of the mining area and the pre-mining period of the unmined area based on the area quota method. The calculation formula for the area quota method is as follows:

[0053] W = ∑W i =∑A i r i (1)

[0054] In the formula, W is the total ecological water requirement of vegetation, in m³. 3 Wi represents the total ecological water requirement for vegetation type i, in m³. 3 Ai is the area of ​​vegetation type i, in meters. 2 ri is the ecological water requirement quota for vegetation type i, in m³. 3 / m 2 .

[0055] S52. For the distribution of vegetation ecological water demand in the mining area during the pre-mining and post-mining periods, perform differential analysis on the thematic layers in ArcGIS to obtain thematic maps of vegetation ecological water shortage distribution in the mining area.

[0056] S6. Extract indicator data and predict the ecological water shortage of vegetation in unmined areas of the mining area based on RBF neural network.

[0057] Further steps are as follows:

[0058] S61. Based on ArcGIS Fishnet functionality, divide the mining area into basic unit grids. To ensure data accuracy, the number of basic unit grids is greater than 100 times the number of boreholes in the area.

[0059] S62. Extract the corresponding indicator data of the basic unit grid in the thematic map of ecological water shortage, coal seam thickness, and drought index of the mining area through the basic unit grid.

[0060] S63. Using the drought index and coal seam thickness of the mining area as input factors and vegetation ecological water shortage as output factors, a vegetation ecological water shortage prediction model is established based on the RBF neural network.

[0061] S64. Based on the prediction model, and combined with the coal seam thickness, drought index and other index data of the basic unit grid in the unmined area of ​​the mining area, predict the thematic map and distribution pattern of ecological water shortage in the unmined area.

[0062] S65. The coefficient of determination is selected as the evaluation index for the above prediction model. The formula for calculating the coefficient of determination is as follows:

[0063]

[0064] In the formula: SSR is the regression sum of squares, and SST is the total sum of squares.

[0065] S7. Apply the distribution patterns of vegetation ecological water shortage to classify the water resource protection levels of mining areas.

[0066] Furthermore, based on the degree of water scarcity in unexploited areas, the water resource protection level of mining areas is classified, providing a theoretical basis for water-conserving coal mining in unexploited areas.

[0067] This embodiment can accurately predict the ecological water shortage of mining areas after large-scale coal mining activities and classify the water resource protection level of mining areas, providing an important theoretical basis for the coordinated development of underground coal resource development and water resource protection in ecologically fragile mining areas.

[0068] Example 2:

[0069] Taking the Northwest mining area as an example, which is an arid and semi-arid region in the northwest, it suffers from water shortages and a fragile ecological and geological environment, making it an ecologically fragile mining area.

[0070] The coal seams in the mining area are 4-8 meters thick and buried at a depth of 300-450 meters. Water-conserving mining techniques need to be considered during the development of coal resources in this area; coal seam mining also has a significant impact on surface vegetation and ecology. Furthermore, the pre-mining and post-mining periods for the mined areas are 1998 and 2016, respectively; the pre-mining period for the unmined areas is 2016. Based on this, this mining area is considered highly representative.

[0071] Based on the steps of the prediction and application method in Example 1, and using collected exploration and meteorological data (1998-2020), the ecological water shortage in the undeveloped area of ​​the mining district is predicted, and the water-conserving coal mining grade of the area is classified. Figure 2 As shown.

[0072] It is evident that the above methods are not only highly practical, but also based on clear principles and are simple and easy to implement. They can accurately predict the ecological water shortage in mining areas after large-scale coal mining activities and classify the water resource protection level of mining areas, providing an important theoretical basis for the coordinated development of underground coal resource development and water resource protection in ecologically fragile mining areas.

[0073] The above description is merely a preferred embodiment of this application and is not intended to limit this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application.

Claims

1. A method for predicting and applying ecological water shortage of vegetation in a mining area, characterized in that, The application relates to a method for predicting vegetation ecological water shortage in a mining area. The method comprises the following steps: acquiring mining area data and acquiring index data of the mining area in different time periods based on satellite remote sensing; acquiring index special topic layers based on a spatial data management tool; defining vegetation ecological water shortage in the mining area, calculating vegetation ecological water demand before and after mining in a mining area, and determining the distribution of vegetation ecological water shortage in the mining area; extracting index data, and predicting vegetation ecological water shortage in an unmined area of the mining area based on a neural network; applying the distribution rule of vegetation ecological water shortage to divide the water resource protection level of the unmined area of the mining area; the prediction process of the vegetation ecological water shortage in the unmined area of the mining area comprises the following steps: dividing a basic unit grid of the mining area; extracting corresponding index data of the basic unit grid in the special topic layers of the ecological water shortage, coal seam thickness and drought index in the mining area; taking the drought index and coal seam thickness of the mining area as input factors, taking the vegetation ecological water shortage as an output factor, and establishing a vegetation ecological water shortage prediction model based on an RBF neural network; 2. The method according to claim 1, characterized in that, predicting the ecological water shortage special topic layer and the distribution rule of the unmined area based on the prediction model and the index data of the basic unit grid in the unmined area.

3. The method according to claim 1, characterized in that, based on the spatial analysis function of ArcGIS and the boundary range of the mining area, a raster special topic layer is drawn, and the land cover type special topic layer of the unmined area in the pre-mining period is drawn.

4. The method according to claim 1, characterized in that, The vegetation ecological water shortage in the mining area is the difference between the vegetation ecological water demand in the pre-mining period and the vegetation ecological water demand in the post-mining period. The vegetation ecological water demand in the pre-mining period and the post-mining period of the mining area and the vegetation ecological water demand in the pre-mining period of the unmined area are calculated based on the area quota method.

5. The method according to claim 4, characterized in that, The vegetation ecological water demand distribution in the pre-mining period and the post-mining period of the mining area is analyzed in the special topic layer of ArcGIS, and the vegetation ecological water shortage distribution special topic layer of the mining area is obtained. In the formula, W is the total ecological water requirement of vegetation, in m3; Wi is the total ecological water requirement of vegetation type i, in m3; Ai is the area of vegetation type i, in m2; and ri is the ecological water requirement quota of vegetation type i, in m3 / m2. 2 2 .​ 6. The method for predicting and applying ecological water shortage of vegetation in a mining area according to claim 1, characterized in that, The calculation formula of the area quota method is: The determination coefficient is selected as the evaluation index of the prediction model, and the calculation formula of the determination coefficient is:

7. The method according to claim 1, characterized in that, In the formula, SSR is the regression sum of squares, and SST is the total sum of squares.

8. The method for predicting and applying ecological water shortage of vegetation in a mining area according to claim 1, characterized in that, The water resource protection level of the mining area is divided according to the water shortage degree of the unmined area.

9. The method for predicting and applying ecological water shortage of vegetation in a mining area according to claim 1, characterized in that, The mining area data comprises geological survey data, mining status data and meteorological data. For the mining area, a set period before mining and a set period after mining are selected; for the unmined area, the set period after mining of the mining area is selected as the pre-mining period of the unmined area.

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