scholarly journals The potential for land erosion due to primary tin mining in Bangka Island

2021 ◽  
Vol 926 (1) ◽  
pp. 012072
Author(s):  
R Hambali ◽  
S Wahyuni

Abstract In the context of primary tin mining by PT. Timah on the Bangka Island, an analysis of environmental impacts is needed concerning various related aspects. One of the potential impacts that need to be considered is erosion due to open land for mining activities. Rain and mining water triggers the process of erosion on open land with particular soil and topographic characteristics. This paper presents an analysis of the potential for erosion due to primary tin mining at five mining locations in Bangka Island. The soil erosion rate can be analyzed using the Universal Soil Loss Equation (USLE) and GIS. The environmental data used to predict the erosion rate include soil type, soil texture and structure, land cover, rainfall, slope, and soil management techniques. In this study, rainfall erosivity is taking into account based on average monthly rainfall from 2010-2019. The results showed that the erosion rates at the primary mining sites are relatively low, ranging from 4.72 to 683.47 tons/ha/year. The results showed that the erosion rate is more influenced by the topography (slope factor). Besides, the considerable land-use change will also contribute significantly to the amount of soil erosion.

Solid Earth ◽  
2018 ◽  
Vol 9 (3) ◽  
pp. 745-757 ◽  
Author(s):  
Selene B. González-Morales ◽  
Alex Mayer ◽  
Neptalí Ramírez-Marcial

Abstract. Variability in physical rates and local knowledge of soil erosion was assessed across six rural communities in the Sierra Madre del Sur, Chiapas, Mexico. The average erosion rate estimated using the RUSLE model is 274 t ha−1 yr−1, with the estimated erosion rates ranging from 28 to 717 t ha−1 yr−1. These very high erosion rates are associated with high rainfall erosivity (17 000 MJ mm ha−1 h−1 yr−1) and steep slopes (mean slope  =  67 %). Many of the highest soil erosion rates are found in communities that are dominated by forestland, but where most of the tree cover has been removed. Conversely, lower erosion rates are often found where corn is cultivated for most of the year. According to the results of the soil erosion KAP (knowledge, attitude and practices) survey, awareness of the concept of soil erosion was reasonably high in all of the communities, but awareness of the causes of erosion was considerably lower. More than half of respondents believed that reforestation is a viable option for reducing soil erosion, but only a third of respondents were currently implementing reforestation practices. Another third of the respondents indicated that they were not following any soil conservation practices. Respondents indicated that adoption of government reforestation efforts have been hindered by the need to clear their land to sell forest products or cultivate corn. Respondents also mentioned the difficulties involved with obtaining favorable tree stocks for reforestation. The KAP results were used to assess the overall level of motivation to solve soil erosion problems by compiling negative responses. The relationship between the magnitude of the soil erosion problem and the capacity to reduce soil erosion is inconsistent across the communities. One community, Barrio Vicente Guerrero, had the highest average negative response rate and the second highest soil erosion rate, indicating that this community is particularly vulnerable.


Author(s):  
Haiyan Fang ◽  
Zemeng Fan

Impact of land use and land cover (LULC) change on soil erosion is still imperfectly understood, especially in northeastern China (NEC). Based on the Revised Universal Loss Equation (RUSLE), the variability of soil erosion at different spatial scales following land use changes in1980, 1990, 2000, 2010, and 2017 was analyzed. The regionally spatial patterns of soil loss coincided with the topography, rainfall erosivity, soil erodibility, and use patterns, and around 45% soil loss came from arable land. Regionally, soil erosion rates increased from 1980 to 2010 and decreased from 2010 to 2017, ranging from 3.91 to 4.45 t ha-1 yr-1 with an average of 4.22 t ha-1 yr-1 in 1980-2017. The rates of soil erosion less than 1.41 t ha-1 yr-1 decreased from 1980 to 2010, and increased from 2010 to 2017, and opposite changing patterns occurred in higher erosion classes (i.e., above 5 t ha-1 yr-1). At a provincial scale, Liaoning Province experienced the highest soil erosion rate of 9.43 t ha-1 yr-1, followed by Jilin Province, the east Inner Mongolia, and Heilongjing Province. Arable land continuously increased at the expense of forest in the high-elevation and steep-slope areas from 1980 to 2010, and decreased from 2010 to 2017, resulting in increased areas with erosion rates higher than 7.05 t ha-1 yr-1. At a county scale, around 75% of the countries had soil erosion rate higher than its tolerance level. The county numbers with higher erosion rate increased in 1980-2010 and decreased in 2010- 2017, resulting from the sprawl and withdrawal of arable land. The results indicate that appropriate policies can control soil loss through limiting arable land sprawl in areas of unfavorable regions in the NEC.


2012 ◽  
Vol 2012 ◽  
pp. 1-7 ◽  
Author(s):  
S. I. Ahmed ◽  
R. P. Rudra ◽  
B. Gharabaghi ◽  
K. Mackenzie ◽  
W. T. Dickinson

This study investigates the effect of rainfall temporal distribution pattern within a storm event on soil erosion rate and the possibility of using rain power type model for rainfall erosivity. Various rainfall distribution patterns, simulated by rainfall simulator, were used on 1.0 m2 plot of silica sand and loam soil with a minimum of three replications. The results show that the soil erosion rates spiked following every sharp increase in rainfall intensity followed by a gradual decline to a steady erosion rate. Transient effects resulted in the soil erosion rates for an oscillatory rainfall distribution to be more than two fold higher than those obtained for a steady-state rainfall intensity event with same duration and same average rainfall intensity. The 3-parameter and 4-parameter rain power models were developed for a process-based measure of rainfall erosivity. The 4 parameter model yielded better match with the observed data and predicted soil erosion rates more accurately for silica sand under all rainfall distributions, and good results for loam soil under low intensity rainfall. More research is necessary to improve the accuracy of soil erosion prediction models for a wider range of rainfall distributions.


2017 ◽  
Author(s):  
Selene B. González-Morales ◽  
Alex Mayer ◽  
Neptalí Ramírez-Marcial

Abstract. The physical aspects and knowledge of soil erosion in six communities in rural Chiapas, Mexico were assessed. Average erosion rates estimated with the RUSLE model ranged from 200 to 1,200 ha−1 yr−1. Most erosion rates are relatively high due to steep slopes, sandy soils and bare land cover. The lowest rates occur where corn is cultivated for much of the year and slopes are relatively low. The results of a knowledge, attitudes and practices (KAP) survey showed that two-thirds of respondents believed that the major cause of soil erosion was hurricanes or rainfall and only 14 % of respondents identified human activities as causes of erosion. Forty-two percent of respondents indicated that the responsibility for solving soil erosion problems lies with government, as opposed to 26 % indicating that the community is responsible. More than half of respondents believed that reforestation is a viable option for reducing soil erosion, but only a third of respondents were currently applying reforestation practices and another one-third indicated that they were not following any conservation practices. The KAP results were used to assess the overall level of knowledge and interest in soil erosion problems and their solutions by compiling negative responses. The community of Barrio Vicente Guerrero may be most vulnerable to soil erosion, since it had the highest average negative response and the second highest soil erosion rate. However, Poblado Cambil had the highest estimated soil erosion rate and a relatively low average negative response rate, suggesting that soil conservation efforts should be prioritized for this community. We conclude that as long as the economic and productive needs of the communities are not solved simultaneously, the risk of soil erosion will increase in the future, which threatens the survival of these communities.


2020 ◽  
Vol 9 (1) ◽  
Author(s):  
Veera Narayana Balabathina ◽  
R. P. Raju ◽  
Wuletaw Mulualem ◽  
Gedefaw Tadele

Abstract Background Soil erosion is one of the major environmental challenges and has a significant impact on potential land productivity and food security in many highland regions of Ethiopia. Quantifying and identifying the spatial patterns of soil erosion is important for management. The present study aims to estimate soil erosion by water in the Northern catchment of Lake Tana basin in the NW highlands of Ethiopia. The estimations are based on available data through the application of the Universal Soil Loss Equation integrated with Geographic Information System and remote sensing technologies. The study further explored the effects of land use and land cover, topography, soil erodibility, and drainage density on soil erosion rate in the catchment. Results The total estimated soil loss in the catchment was 1,705,370 tons per year and the mean erosion rate was 37.89 t ha−1 year−1, with a standard deviation of 59.2 t ha−1 year−1. The average annual soil erosion rare for the sub-catchments Derma, Megech, Gumara, Garno, and Gabi Kura were estimated at 46.8, 40.9, 30.9, 30.0, and 29.7 t ha−1 year−1, respectively. Based on estimated erosion rates in the catchment, the grid cells were divided into five different erosion severity classes: very low, low, moderate, high and extreme. The soil erosion severity map showed about 58.9% of the area was in very low erosion potential (0–1 t ha−1 year−1) that contributes only 1.1% of the total soil loss, while 12.4% of the areas (36,617 ha) were in high and extreme erosion potential with erosion rates of 10 t ha−1 year−1 or more that contributed about 82.1% of the total soil loss in the catchment which should be a high priority. Areas with high to extreme erosion severity classes were mostly found in Megech, Gumero and Garno sub-catchments. Results of Multiple linear regression analysis showed a relationship between soil erosion rate (A) and USLE factors that soil erosion rate was most sensitive to the topographic factor (LS) followed by the support practice (P), soil erodibility (K), crop management (C) and rainfall erosivity factor (R). Barenland showed the most severe erosion, followed by croplands and plantation forests in the catchment. Conclusions Use of the erosion severity classes coupled with various individual factors can help to understand the primary processes affecting erosion and spatial patterns in the catchment. This could be used for the site-specific implementation of effective soil conservation practices and land use plans targeted in erosion-prone locations to control soil erosion.


2021 ◽  
Vol 8 (1) ◽  
pp. 26
Author(s):  
Manti Patil ◽  
Radheshyam Patel ◽  
Arnab Saha

Soil erosion is one of the most critical environmental hazards of recent times. It broadly affects to agricultural land and reservoir sedimentation and its consequences are very harmful. In agricultural land, soil erosion affects the fertility of soil and its composition, crop production, soil quality and land quality, yield and crop quality, infiltration rate and water holding capacity, organic matter and plant nutrient and groundwater regimes. In reservoir sedimentation process the consequences of soil erosion process are reduction of the reservoir capacity, life of reservoir, water supply, power generation etc. Based on these two aspects, an attempt has been made to the present study utilizing Revised Universal Soil Loss Equation (RUSLE) has been used in integration with remote sensing and GIS techniques to assess the spatial pattern of annual rate of soil erosion, average annual soil erosion rate and erosion prone areas in the MAN catchment. The RUSLE considers several factors such as rainfall, soil erodibility, slope length and steepness, land use and land cover and erosion control practice for soil erosion prediction. In the present study, it is found that average annual soil erosion rate for the MAN catchment is 13.01-tons/ha/year, which is higher than that of adopted and recommended values for the project. It has been found that 53% area of the MAN catchment has negligible soil erosion rate (less than 2-tons/ha/year). Its spatial distribution found on flat land of upper MAN catchment. It has been detected that 26% area of MAN catchment has moderate to extremely severe soil erosion rate (greater than 10-tons/ha/year). Its spatial distribution has been found on undulated topography of the middle MAN catchment. It is proposed to treat this area by catchment area treatment activity.


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