scholarly journals Evolution Pattern of Tailings Flow from Dam Failure and the Buffering Effect of Debris Blocking Dams

Water ◽  
2019 ◽  
Vol 11 (11) ◽  
pp. 2388 ◽  
Author(s):  
Guangjin Wang ◽  
Sen Tian ◽  
Bin Hu ◽  
Zhifa Xu ◽  
Jie Chen ◽  
...  
Keyword(s):  
Dam Failure ◽  
Environmental Disaster ◽  
Tailings Pond ◽  
Evolution Pattern ◽  
Evolution Characteristics ◽  
Downstream Section ◽  
Production And Operation ◽  
Tailings Ponds ◽  
Important Basis ◽  
Post Disaster

Tailings ponds are the indispensable facilities in the mine production and operation. Once the dam is destabilized and damaged, it will pose a serious threat on the life and property of the downstream population and could also potentially cause an environmental disaster. With an engineering background, this paper dynamically and numerically simulates the evolution process of tailings flow from dam failure and the influence scope of any resulting disaster in context. The evolution characteristics of leaked tailings flow are analyzed at various downstream riverbed slopes and debris blocking dam settings. In addition, parameters such as flow rate, impact force and deposition range of leaked tailings flow at downstream arrival are studied, as well as their correlations. The results indicate that the flat terrains upstream and downstream of passage zone show a relatively larger area of inundation by tailings flow. Both the maximum and final downstream inundated ranges increase with the elevating slope of downstream riverbed, and the leaked tailings are deposited mainly in the nearby villages in front of the dam and the flat terrains of the downstream passage zone. Additionally, rational establishment of debris blocking dams on the downstream side is effective in diminishing the damage of tailings flow to the downstream section. This study can also provide an important basis for the quantitative evaluation of post-disaster influence scope for tailings pond as well as for the design of dam body.

scholarly journals An Improved Faster R-CNN Method to Detect Tailings Ponds from High-Resolution Remote Sensing Images

2021 ◽  
Vol 13 (11) ◽  
pp. 2052
Author(s):  
Dongchuan Yan ◽  
Guoqing Li ◽  
Xiangqiang Li ◽  
Hao Zhang ◽  
Hua Lei ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Deep Learning ◽  
High Resolution ◽  
High Precision ◽  
Large Scale ◽  
Dam Failure ◽  
Remote Sensing Images ◽  
Feature Maps ◽  
Tailings Pond ◽  
Tailings Ponds

Dam failure of tailings ponds can result in serious casualties and environmental pollution. Therefore, timely and accurate monitoring is crucial for managing tailings ponds and preventing damage from tailings pond accidents. Remote sensing technology facilitates the regular extraction and monitoring of tailings pond information. However, traditional remote sensing techniques are inefficient and have low levels of automation, which hinders the large-scale, high-frequency, and high-precision extraction of tailings pond information. Moreover, research into the automatic and intelligent extraction of tailings pond information from high-resolution remote sensing images is relatively rare. However, the deep learning end-to-end model offers a solution to this problem. This study proposes an intelligent and high-precision method for extracting tailings pond information from high-resolution images, which improves deep learning target detection model: faster region-based convolutional neural network (Faster R-CNN). A comparison study is conducted and the model input size with the highest precision is selected. The feature pyramid network (FPN) is adopted to obtain multiscale feature maps with rich context information, the attention mechanism is used to improve the FPN, and the contribution degrees of feature channels are recalibrated. The model test results based on GoogleEarth high-resolution remote sensing images indicate a significant increase in the average precision (AP) and recall of tailings pond detection from that of Faster R-CNN by 5.6% and 10.9%, reaching 85.7% and 62.9%, respectively. Considering the current rapid increase in high-resolution remote sensing images, this method will be important for large-scale, high-precision, and intelligent monitoring of tailings ponds, which will greatly improve the decision-making efficiency in tailings pond management.

Water Quality From Gualaxo Do Norte And Carmo Rivers (Minas Gerais, Brazil) After The Fundão Dam Failure

2021 ◽  
Vol 44 ◽  
Author(s):  
Leonardo Brandão Nogueira ◽  
Sabriny Melo Sousa ◽  
Camila Gonçalves Lobo Santos ◽  
Gustavo Simões Araújo ◽  
Laser Oliveira ◽  
...  
Keyword(s):  
Water Quality ◽  
Trace Elements ◽  
Rainy Season ◽  
Aquatic Ecosystems ◽  
Dam Failure ◽  
Subsistence Farming ◽  
Environmental Disaster ◽  
Uncertain Future ◽  
Toxic Potential

Mining waste is rich in trace elements, which present a high toxic potential and may represent a risk for aquatic ecosystems. The Fundão dam failure, considered the largest environmental disaster in the world, affected 663.2 km of watercourses, including Carmo and Gualaxo do Norte Rivers. The ore tail also affected the riverside communities, destroying villages, killing people and affecting the subsistence farming. To evaluate the influence of the mine tailing wave on the water quality of the Carmo and Gualaxo do Norte Rivers water samples were collected at nine points located in Barra Longa during the rainy season. Physicochemical parameters (conductivity, resistivity, EH, total dissolved solids, pH and temperature) and major, minor and trace elements concentrations (Ba, Co, Cr, Cu, Ni, Sc, Sr, V, Zn, As, Pb, Al, Fe, Mn, Ca, K, Mg and P) were evaluated and compared with previous studies and conformity limits established by a national resolution (CONAMA Resolution N°357/2005). Only conductivity, Fe and Mn presented non-conformity values according to CONAMA Resolution N°357/2005. These results may be related not only to the dam burst but also to the rainy season and non-detectable pollution sources. Furthermore, the decreased levels in the toxic elements in the rivers over time, may be related to its association with sediments in addition to their flux to the Atlantic Ocean. Thus, after nearly six years, the environmental and social impacts are still alive and the minerals dragged to the riverbed could bring cumulative effects for the entire environment what means an uncertain future to the Rio Doce Basin and adjacent coastal zone.

scholarly journals Concentrating Mill Wastes are the Source of Pollution of Human Environment and Natural Ecosystems with Heavy Metals: A Case Study in Primorsky Krai, Russian Federation

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Irina A. Tarasenko ◽  
Alexander V. Zin’kov ◽  
Aleksei S. Kholodov ◽  
Muhammad Riaz ◽  
Valeriy I. Petukhov ◽  
...  
Keyword(s):  
Heavy Metals ◽  
Russian Federation ◽  
Negative Impact ◽  
Software Modeling ◽  
Natural Ecosystems ◽  
Primorsky Krai ◽  
Human Environment ◽  
Tailings Pond ◽  
Hazardous Elements ◽  
Tailings Ponds

Elevated contents of hazardous elements in natural ecosystems are often associated with human activities. Significant quantities of these elements, including heavy metals, are concentrated in tailings. The goal of the study was to assess the mineralogical and geochemical features of the old tailings of the decommissioned Krasnorechenskaya concentrating mill (located in Primorsky Krai, Russian Federation), which was processing complex tin-polymetallic and silver-lead-zinc ores, the chemical features of tailings pond waters, and the extent of environmental impact on the nearby Rudnaya river. In addition to the analysis of rock and water samples, the software modeling of the water-rock-gas system was carried out. In the study area, the minerals and rocks undergo changes that lead to the formation of highly mineralized, acidic waters saturated with various elements. In the tailings ponds, the maximum permissible concentrations were exceeded for Zn, Cd, Cu, Mg, Fetotal, Pb, Mn, Al, As, Co, Be, Sr, Ni, and Ba. The drainage from the tailings pond tripled the total mineralization of the Rudnaya river relative to the background values. However, the intoxication of the ecosystem by tailing products is partially inhibited by the secondary minerals in the tailings ponds. The negative impact is of a local nature, and 500 m downstream the concentration of many of the above elements is reduced. Despite this, the system that forms the chemical composition of highly mineralized waters is far from the equilibrium state. The oxidation of sulfides, dissolution of other minerals, and migration of oxidation and hydrolysis products will continue affecting the environment. In this regard, it is necessary to conduct environmental monitoring and undertake activities aimed at the recovery of mature concentration tailings or at suppressing the activity of hazardous elements by the conservation of tailings ponds.

scholarly journals Integration of DSM and SPH to Model Tailings Dam Failure Run-Out Slurry Routing Across 3D Real Terrain

Water ◽  
2018 ◽  
Vol 10 (8) ◽  
pp. 1087 ◽  
Author(s):  
Kun Wang ◽  
Peng Yang ◽  
Karen Hudson-Edwards ◽  
Wensheng Lyu ◽  
Chao Yang ◽  
...  
Keyword(s):  
Numerical Modelling ◽  
Physical Modelling ◽  
Dam Failure ◽  
Surface Model ◽  
Tailings Dam ◽  
Disaster Prevention ◽  
Sph Method ◽  
Tailings Pond ◽  
Dam Failures ◽  
Modelling Experiment

Tailings dam failure accidents occur frequently, causing substantial damage and loss of human and animal life. The prediction of run-out tailings slurry routing following dam failures is of great significance for disaster prevention and mitigation. Using satellite remote sensing digital surface model (DSM) data, tailings pond parameters and the advanced meshless smoothed particle hydrodynamics (SPH) method, a 3D real-scale numerical modelling method was adopted to study the run-out tailings slurry routing across real downstream terrains that have and have not been affected by dam failures. Three case studies, including a physical modelling experiment, the 2015 Brazil Fundão tailings dam failure accident and an operating high-risk tailings pond in China, were carried out. The physical modelling experiment and the known consequences were successfully modeled and validated using the SPH method. This and the other experiments showed that the run-out tailings slurry would be tremendously destructive in the early stages of dam failure, and emergency response time would be extremely short if the dam collapses at its full designed capacity. The results could provide evidence for disaster prevention and mitigation engineering, emergency management plan optimization, and the development of more responsible site plans and sustainable site designs. However, improvements such as rheological model selection, terrain data quality, computing efficiency and land surface roughness need to be made for future studies. SPH numerical modelling is a powerful and advanced technique that is recommended for hazard assessment and the sustainable design of tailings dam facilities globally.

scholarly journals Complete Genome Sequence of a Pseudomonas Species Isolated from Tailings Pond Water in Alberta, Canada

2021 ◽  
Vol 10 (9) ◽  
Author(s):  
Steven Shideler ◽  
John Headley ◽  
Jeff Gauthier ◽  
Irena Kukavica-Ibrulj ◽  
Roger C. Levesque ◽  
...  
Keyword(s):  
Genome Sequence ◽  
Complete Genome Sequence ◽  
Oil Sands ◽  
Complete Genome ◽  
Pond Water ◽  
Toxic Compounds ◽  
Tailings Pond ◽  
Pseudomonas Species ◽  
Tailings Ponds ◽  
Oil Sands Tailings Ponds

ABSTRACT We report the complete genome sequence of strain OST1909, belonging to a Pseudomonas species. The genome size is 6,306,352 bp, with a G+C content of 59.6%. The isolate was recovered from oil sands process-affected water (OSPW), despite the numerous toxic compounds that accumulate in oil sands tailings ponds.

scholarly journals Tailings From Mining Activities, Impact on Groundwater, and Remediation

2001 ◽  
Vol 6 (2) ◽  
pp. 35
Author(s):  
Khalid Al-Rawahy
Keyword(s):  
Waste Water ◽  
Suspended Solids ◽  
Mining Industry ◽  
Mining Activities ◽  
Dissolved Metals ◽  
Mining Operations ◽  
Metal Pollutants ◽  
Tailings Pond ◽  
Potential Groundwater ◽  
Tailings Ponds

Effluent wastes from mining operations and beneficiation processes are comprized mostly of the following pollutants: total suspended solids (TTS), alkalinity or acidity (pH), settleable solids, iron in ferrous mining, and dissolved metals in nonferrous mining. Suspended solids consist of small particles of solid pollutants that resist separation by conventional means. A number of dissolved metals are considered toxic pollutants. The major metal pollutants present in ore mining and beneficiation waste waters include arsenic, cadmium, copper, lead, mercury, nickel, and zinc. Tailings ponds are used for both the disposal of solid waste and the treatment of waste-water streams. The supernatant decanted from these ponds contains suspended solids and, at times, process reagents introduced to the water during ore beneficiation. Leakage of material from tailings pond into groundwater is one possible source of water pollution in the mining industry. Percolation of waste-water from impoundment may occur if tailings ponds are not properly designed. This paper addresses potential groundwater pollution due to effluent from mining activities, and the possible remediation options.

scholarly journals Improved Method to Detect the Tailings Ponds from Multispectral Remote Sensing Images Based on Faster R-CNN and Transfer Learning

2021 ◽  
Vol 14 (1) ◽  
pp. 103
Author(s):  
Dongchuan Yan ◽  
Hao Zhang ◽  
Guoqing Li ◽  
Xiangqiang Li ◽  
Hua Lei ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Deep Learning ◽  
Object Detection ◽  
Transfer Learning ◽  
Near Infrared ◽  
Image Data ◽  
Remote Sensing Images ◽  
Tailings Pond ◽  
True Color ◽  
Tailings Ponds

The breaching of tailings pond dams may lead to casualties and environmental pollution; therefore, timely and accurate monitoring is an essential aspect of managing such structures and preventing accidents. Remote sensing technology is suitable for the regular extraction and monitoring of tailings pond information. However, traditional remote sensing is inefficient and unsuitable for the frequent extraction of large volumes of highly precise information. Object detection, based on deep learning, provides a solution to this problem. Most remote sensing imagery applications for tailings pond object detection using deep learning are based on computer vision, utilizing the true-color triple-band data of high spatial resolution imagery for information extraction. The advantage of remote sensing image data is their greater number of spectral bands (more than three), providing more abundant spectral information. There is a lack of research on fully harnessing multispectral band information to improve the detection precision of tailings ponds. Accordingly, using a sample dataset of tailings pond satellite images from the Gaofen-1 high-resolution Earth observation satellite, we improved the Faster R-CNN deep learning object detection model by increasing the inputs from three true-color bands to four multispectral bands. Moreover, we used the attention mechanism to recalibrate the input contributions. Subsequently, we used a step-by-step transfer learning method to improve and gradually train our model. The improved model could fully utilize the near-infrared (NIR) band information of the images to improve the precision of tailings pond detection. Compared with that of the three true-color band input models, the tailings pond detection average precision (AP) and recall notably improved in our model, with the AP increasing from 82.3% to 85.9% and recall increasing from 65.4% to 71.9%. This research could serve as a reference for using multispectral band information from remote sensing images in the construction and application of deep learning models.

scholarly journals The impact of the Brumadinho dam failure in Naô Xohâ village

2019 ◽  
Vol 10 (3) ◽  
pp. 179-211
Author(s):  
Adriana Aparecida Silva ◽  
Divina Aparecida Leonel Lunas ◽  
Poliene Soares dos Santos Bicalho ◽  
Roseli Martins Tristão Maciel
Keyword(s):  
Social Groups ◽  
Interdisciplinary Approach ◽  
Environmental Issues ◽  
Dam Failure ◽  
Strong Impact ◽  
Review Of The Literature ◽  
Press Releases ◽  
Environmental Disaster ◽  
The Impact ◽  
The Village

It is still under strong impact from the Brumadinho dam failure that this article was written. Our main goal is to approach, in the midst of so many social groups hit by this announced tragedy, the reality of the village Naô Xohã, whose population lives on the banks of the Paraopeba River, also victimized by this environmental disaster of consequences not yet dimensioned. As it is a contemporary theme, several press releases were used to compose the narrative, as well as to build a comprehensive review of the literature on the Movement of People Affected by Dams and on socioeconomic and environmental impacts. The proposition, however, is based on an interdisciplinary approach to the theme, which is the impact of the Brumadinho dam failure in Naô Xohã village, mainly due to the pollution that spread over the Paraopeba River. To this end, a fruitful dialogue was established between history, geography, economics and environmental issues.

scholarly journals A Tethered And Navigated Air Blimp (TANAB) for observing themicroclimate over a complex terrain

2019 ◽  
Author(s):  
Manoj K. Nambiar ◽  
Ryan A. E. Byerlay ◽  
Amir Nazem ◽  
M. Rafsan Nahian ◽  
Mohsen Moradi ◽  
...  
Keyword(s):  
Thermal Imaging ◽  
Complex Terrain ◽  
Turbulence Statistics ◽  
Cfd Simulations ◽  
Transport Models ◽  
Future Studies ◽  
Tailings Pond ◽  
Emission Fluxes ◽  
Computational Fluid Dynamics Cfd ◽  
Tailings Ponds

Abstract. This study presents the first environmental monitoring field campaign of a newly developed Tethered And Navigated Air Blimp (TANAB) system to investigate the microclimate over a complex terrain. The use of a tethered balloon in complex terrains such as mines and tailings ponds is novel and the focus of the present study. The TANAB system was fully developed and launched at a mine facility in northern Canada in May 2018. This study describes the key design features, the sensor payload onboard, and the observations made by the TANAB system. The system measured meteorological conditions including wind speed in three directions, temperature, relative humidity, and pressure over the first few tens of meters of the atmospheric boundary layer. The system also performed earth surface thermal imaging, or temperature mapping, of the underlying surface. The measurements were made at two primary locations in the facility: i) near a tailings pond and ii) in a mine pit. TANAB measured the dynamics of the atmosphere at different diurnal times (e.g. day versus night) and locations (near tailings pond versus inside the mine). Such dynamics include mean and turbulence statistics pertaining to flow momentum and energy, and they are crucial in the understanding of emission fluxes from the facility in future studies. In addition, TANAB can provide boundary conditions and validation datasets to support mesoscale dispersion modelling or Computational Fluid Dynamics (CFD) simulations for various transport models.

scholarly journals Model Test Study on Dam Failure in Tailings Pond

2019 ◽  
Vol 304 ◽  
pp. 022057
Author(s):  
Qinglan Qi ◽  
Liting Zhang ◽  
Xiaogang Wang ◽  
Shaoxiong Zhang ◽  
Fei Lv
Keyword(s):  
Model Test ◽  
Dam Failure ◽  
Tailings Pond ◽  
Test Study
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