矿产资源开发会造成一定程度的水土流失。例如露天开采形成采空区，导致地面

The development of mineral resources will cause a certain degree of soil erosion. For example, open-pit mining forms a goaf, which leads to ground subsidence and subsidence. The development of mineral resources will also cut down trees, occupy land, and pollute the soil, causing soil quality to be destroyed. These may lead to increased soil erosion near the mining area. <br>The analysis of the impact of mineral resources development on soil erosion in this article is mainly to analyze the relationship between soil erosion in mining areas and the content of Cu, Zn and other metal elements in the soil collected in the mining area. Based on the results of the 2009 soil erosion classification in the study area obtained in Chapter 4 according to the genetic neural network algorithm, the abundance and average value of Cu, Zn and other metal elements in the soil of each soil erosion level area are calculated, and the results are shown in Figure 7. <br>It can be seen from Figure 8 that the abundance of metal elements in the soil is higher in the areas with lower soil erosion. The average is relatively high. Conversely, the more serious the soil erosion, the lower the content of metal elements in the soil. This shows that the content of metal elements in the soil will be diluted with soil erosion, and the impact of mineral resource development on areas with weak soil erosion is greater than that of areas with intense soil erosion. <br>If the buffer radius is too large, the water quality response unit formed by the buffer will be outside the mining area. At the same time, considering that the resolution of the TM data used for this land use information extraction is 30m, the radius is too small to extract the land type information Can not truly reflect the actual situation on the surface. Based on the results of previous studies and the actual situation of the study area, 1500m is finally selected as the buffer radius of the monitoring point of the river water quality section through the experiment. Taking the sampling point as the center, establish a buffer zone with a radius of 1500m, and then analyze the distribution of geochemical elements in the buffer zone. The <br>micro-scale research shown in Figure 9 takes the small watersheds and buffer zones upstream and downstream of the mining area as the research unit, and counts the average and abundance of pollutant elements in each area, and discusses mineral resources based on this. Develop and compare the impact of development on small watersheds and buffer zones. Then analyze the spatial variation of the relevant metal element content in the water system, soil and water system sediments of the sampling points in the small watershed and buffer zone from upstream to downstream with the flow of a certain river. And further analyze the impact of mineral resources development on land cover types, vegetation coverage, biodiversity and other factors. As shown in Figure 10<br>The analysis of the buffer zone and the small watershed scale shows that the two abundance indexes and the average value of the chemical element content are used as the basis for the research. Use the regional statistics function to calculate the interpolation results of the Cu element content in the sediments of the entire watershed, and obtain the maximum, minimum, standard deviation and mean value of the content in each small watershed and buffer zone, and calculate two Abundance index, one of which is CaCb, the other abundance index is Cm/Cb. The specific results are shown in Table 8.

The exploitation of mineral resources will cause a certain degree of soil erosion. For example, open-pit mining forms a mining area, resulting in ground subsidence and collapse. The exploitation of mineral resources can also cut down trees, occupy land, and pollute the soil, causing damage to the soil. All of this can lead to increased soil erosion near the mine.<br>In this paper, the impact of mineral resources development on soil erosion is mainly analyzed in the mining area soil erosion and mining areas in the soil of Cu, and Zn and other metal elements content. Based on the results of soil erosion classification in the study area in 2009 based on the genetic neural network algorithm in Chapter 4 above, the abundance and mean of metal elements such as Cu and Zn in each soil loss level area are counted, as shown in Figure 7.<br>It can be seen from Figure 8 that the abundance value of metal elements in soil in areas with low soil erosion is high. The mean is also relatively high. On the contrary, the more serious soil erosion, the lower the metal content in the soil. Thus, the content of metal elements in soil will be diluted with soil erosion, and the impact of mineral resources development on the weaker areas of soil erosion is greater than that of intensity soil erosion.<br>The selection of buffer radius such as too large buffer formed water quality response units are mostly outside the mining area, taking into account that the TM data used for this land use information extraction resolution of 30m, the radius is too small to extract the earth-type information can not truly reflect the actual situation on the surface. According to the results of previous research experience, combined with the actual situation of the study area, 1500m was finally selected as the buffer radius of the river water quality section monitoring point. With the sampling point as the center, a buffer with a radius of 1500m is established, and the distribution of the inland elements of the buffer is analyzed. As shown in Figure 9<br>The microscale study takes the small basins and buffer zones upstream and downstream of the water system in the mining area as the research unit, and counts the average and abundance data results of the pollution element content in each region, so as to discuss the impact of mineral resources development on small basins and buffer zones and compare them. The content of related metal elements in water system, soil and water sediments at sampling points in small basins and buffer zones is then analyzed with the spatial changes of a river flowing from upstream to downstream. The influence of mineral resources development on land cover type, vegetation cover and biodiversity is further analyzed. As shown in Figure 10<br>The analysis of buffer and small basin scales shows that the two abundance indices and averages of chemical element content are used for research. Using the regional statistics function, the interpolation results of Cu element content values in water system sediments in the whole basin were calculated, the maximum, minimum, standard deviation and mean values of content values in each small basin and buffer were obtained, and two abundance indices were calculated, one for CaCb and the other for Cm/Cb. The results are shown in Table 8.

The exploitation of mineral resources will cause soil erosion to a certain extent. For example, open-pit mining forms goaf, which leads to land subsidence and collapse. The exploitation of mineral resources will also cut down trees, occupy land, pollute the soil and destroy the soil. All these may lead to the aggravation of soil erosion near the mining area.<br>In this paper, the impact of mineral resources development on soil erosion is mainly to analyze the relationship between soil erosion and the content of Cu, Zn and other metal elements in the mining soil. According to the soil and water loss classification results in 2009 obtained by genetic neural network algorithm in Chapter 4 of the previous paper, the abundance and mean value of Cu, Zn and other metal elements in soil of each soil and water loss level area are counted. The results are shown in Figure 7.<br>It can be seen from figure 8 that the abundances of metal elements in soil are higher in areas with lower soil and water loss. The average value is relatively high. On the contrary, the more serious the soil erosion, the lower the content of metal elements in the soil. The results show that the content of metal elements in soil will be diluted with soil erosion, and the influence of mineral resources development on the weak soil erosion area is greater than that on the strong soil erosion area.<br>If the buffer radius is too large, the water quality response unit formed by the buffer is outside the scope of the mining area. At the same time, considering that the resolution of TM data used for this land use information extraction is 30m, the radius is too small, the extracted land type information can not truly reflect the actual situation of the surface. According to the results of previous research experience, combined with the actual situation of the study area, 1500m was selected as the buffer radius of the river water quality monitoring point. Taking the sampling point as the center, a buffer with a radius of 1500m is established, and then the distribution of localized elements in the buffer is analyzed. As shown in Figure 9<br>The micro scale research takes the small watershed and buffer zone in the upstream and downstream of the mining water system as the research unit, counts the average value and abundance of pollution elements in each region, and discusses the impact of mineral resources development on the small watershed and buffer zone, and compares them. Then, the spatial variation of metal element contents in water system, soil and stream sediment of sampling points in small watershed and buffer zone from upstream to downstream was analyzed. Furthermore, the effects of mineral resources development on land cover type, vegetation coverage and biodiversity were analyzed. As shown in Figure 10<br>Buffer zone and small watershed scale analysis showed that the content of chemical elements was based on two abundance indices and average values. By using the regional statistical function, the interpolation results of Cu content in stream sediments of the whole watershed were statistically analyzed, and the maximum, minimum, standard deviation and mean value of Cu content in each small watershed and buffer zone were obtained, and two abundance indices were calculated, one was CACB, the other was cm / CB. The specific results are shown in Table 8.<br>