Estimation of soil erosion and sediment yield from mine tailing dumps using GIS: a case study at the Samgwang mine, Korea

Kim, Sung-Min; Choi, Yosoon; Suh, Jangwon; Oh, Sungchan; Park, Hyeong‐Dong; Yoon, Suk-Ho

doi:10.1080/12269328.2012.674426

Cited by 33 publications

(14 citation statements)

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“…In this regard, quantitative assessment of soil erosion is a key to infer the extent and magnitude of the problem and identification of more vulnerable sites. Different model based methods has been developed for soil erosion spatial assessment and quantification (Kim et al 2012;Zhang et al 2009). The revised universal soil loss equation (RUSLE) (Renard et al 1997) with its integration to geographic information system (GIS) is among widely applied empirical models for assessment of sheet, inter-rill and rill erosion.…”

Section: Introductionmentioning

confidence: 99%

Potential soil erosion estimation and area prioritization for better conservation planning in Gumara watershed using RUSLE and GIS techniques’

2019

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Background: Water induced soil erosion has been continued to threaten the land resources in sub humid northwestern highlands of Ethiopia. Soil and water conservation measures have been implemented without site-specific scientifically quantified soil erosion data and priority bases. In this regard, quantitative analysis of soil erosion and its spatial variation plays a decisive role for better evidence and priority based implementation. Thus, this study aimed to estimate potential soil loss, identify hotspot areas, and prioritize for conservation measures in Gumara watershed using RUSLE, GIS and remote sensing techniques'. Result: The study result showed that soil loss due to water erosion was found to be a critical problem in the watershed. It ranges from nearly zero in gentle slope of forest lands to 442.92 t ha −1 year −1 on very steep slope cultivated lands. A total of 9.683456 million t of gross surface soil has been lost annually, with an average soil erosion rate of 42.67 t ha −1 year −1. Of which 62.1% was generated from cultivated land. The model result indicated a high spatial variability of soil erosion within the watershed. High intensity of soil erosion has been principally attributed to slope and land use/covers. The study further estimated that about 63.1% of the total soil loss was generated from only 29.3% of the area delineated as very severe soil erosion severity class. Soil erosion rate for 71.7% of the watershed area was beyond the maximum tolerable soil erosion limit estimated for Ethiopian highlands (> 18 t ha −1 year −1). The subwatershed severity class map revealed that 3814 ha of the sub-watershed area was evaluated as very severe level of soil erosion severity class. Conclusion: Soil erosion in the watershed has been a threatening problem for agricultural production to day, its sustainability and to be worsening in the future unless remedial measures were taken, mainly due to human intervention. Therefore, Gumara watershed needs immediate intervention for better conservation planning by considering identified priority classes and hotspot areas.

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Section: Introductionmentioning

confidence: 99%

Potential soil erosion estimation and area prioritization for better conservation planning in Gumara watershed using RUSLE and GIS techniques’

2019

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“…Elevated concentrations of PTEs in soil do not only impact the soil quality, but due to their persistent nature and long biological half-lives, can accumulate in the food chain and can eventually influence human health [ 4 ]. Therefore, the type, content and spatial variation of PTEs in soil should be regularly investigated at both operating and abandoned mining areas to identify the proper measures necessary for preventing soil contamination [ 5 , 6 ].…”

Section: Introductionmentioning

confidence: 99%

Mapping Copper and Lead Concentrations at Abandoned Mine Areas Using Element Analysis Data from ICP–AES and Portable XRF Instruments: A Comparative Study

Lee

Choi

Suh

et al. 2016

IJERPH

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Understanding spatial variation of potentially toxic trace elements (PTEs) in soil is necessary to identify the proper measures for preventing soil contamination at both operating and abandoned mining areas. Many studies have been conducted worldwide to explore the spatial variation of PTEs and to create soil contamination maps using geostatistical methods. However, they generally depend only on inductively coupled plasma atomic emission spectrometry (ICP–AES) analysis data, therefore such studies are limited by insufficient input data owing to the disadvantages of ICP–AES analysis such as its costly operation and lengthy period required for analysis. To overcome this limitation, this study used both ICP–AES and portable X-ray fluorescence (PXRF) analysis data, with relatively low accuracy, for mapping copper and lead concentrations at a section of the Busan abandoned mine in Korea and compared the prediction performances of four different approaches: the application of ordinary kriging to ICP–AES analysis data, PXRF analysis data, both ICP–AES and transformed PXRF analysis data by considering the correlation between the ICP–AES and PXRF analysis data, and co-kriging to both the ICP–AES (primary variable) and PXRF analysis data (secondary variable). Their results were compared using an independent validation data set. The results obtained in this case study showed that the application of ordinary kriging to both ICP–AES and transformed PXRF analysis data is the most accurate approach when considers the spatial distribution of copper and lead contaminants in the soil and the estimation errors at 11 sampling points for validation. Therefore, when generating soil contamination maps for an abandoned mine, it is beneficial to use the proposed approach that incorporates the advantageous aspects of both ICP–AES and PXRF analysis data.

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“…Enriched PTEs in soil not only cause soil contamination but influence human health via the food chain [1,2,3,4,5]. To minimize the risk that arises from the high level of PTEs in soil, an examination of the extent and the level of contamination based on environmental assessment and monitoring is an important first step towards appropriate remediation [6,7].…”

Section: Introductionmentioning

confidence: 99%

A Rapid, Accurate, and Efficient Method to Map Heavy Metal-Contaminated Soils of Abandoned Mine Sites Using Converted Portable XRF Data and GIS

Suh

Lee

Choi

2016

IJERPH

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The use of portable X-ray fluorescence (PXRF) and inductively coupled plasma atomic emission spectrometry (ICP-AES) increases the rapidity and accuracy of soil contamination mapping, respectively. In practice, it is often necessary to repeat the soil contamination assessment and mapping procedure several times during soil management within a limited budget. In this study, we have developed a rapid, inexpensive, and accurate soil contamination mapping method using a PXRF data and geostatistical spatial interpolation. To obtain a large quantity of high quality data for interpolation, in situ PXRF data analyzed at 40 points were transformed to converted PXRF data using the correlation between PXRF and ICP-AES data. The method was applied to an abandoned mine site in Korea to generate a soil contamination map for copper and was validated for investigation speed and prediction accuracy. As a result, regions that required soil remediation were identified. Our method significantly shortened the time required for mapping compared to the conventional mapping method and provided copper concentration estimates with high accuracy similar to those measured by ICP-AES. Therefore, our method is an effective way of mapping soil contamination if we consistently construct a database based on the correlation between PXRF and ICP-AES data.

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Estimation of soil erosion and sediment yield from mine tailing dumps using GIS: a case study at the Samgwang mine, Korea

Cited by 33 publications

References 14 publications

Potential soil erosion estimation and area prioritization for better conservation planning in Gumara watershed using RUSLE and GIS techniques’

Potential soil erosion estimation and area prioritization for better conservation planning in Gumara watershed using RUSLE and GIS techniques’

Mapping Copper and Lead Concentrations at Abandoned Mine Areas Using Element Analysis Data from ICP–AES and Portable XRF Instruments: A Comparative Study

A Rapid, Accurate, and Efficient Method to Map Heavy Metal-Contaminated Soils of Abandoned Mine Sites Using Converted Portable XRF Data and GIS

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