Effects of Coal Mining on Shallow Water Resources in Semiarid Regions: A Case Study in the Shennan Mining Area, Shaanxi, China

Qiao, Wei; Li, Wenping; Li, Tao; Chang, Jinyuan; Wang, Qiqing

doi:10.1007/s10230-016-0414-4

Cited by 96 publications

(26 citation statements)

References 10 publications

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“…The mean annual temperature is 15 C, while the maximum and minimum mean annual temperatures range between 24.8 and 3.6 C, respectively. The maximum mean annual rainfall varies from 400 to 800 mm and is concentrated primarily between May and August (Qiao et al 2017;Wang et al 2018a). The Bailong and Baishui Rivers, running from west to east into Jialing River, are among the larger river systems within the boundary of the Wen County.…”

Section: Study Areamentioning

confidence: 99%

Predictive modeling of landslide hazards in Wen County, northwestern China based on information value, weights-of-evidence, and certainty factor

Wang

Guo

et al. 2019

Geomatics, Natural Hazards and Risk

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Landslide susceptibility mapping is essential in delineating landslide prone areas in mountainous regions. The primary purpose of this study is to evaluate landslide susceptibility mapping using three methods, information value (IV), weights-of-evidence (WofE), and certainty factor (CF) in southeastern Gansu province, China. Firstly, the landslide in the study area was located mainly using aerial-photo interpretation and field surveys. A total of 529 landslides were randomly divided using a ratio of 70/30 for training and validation of these methods. Eight landslide conditioning factors including slope angle, altitude, NDVI, distance to faults, distance to roads, distance to rivers, rainfall, and lithology, were considered. Landslide susceptibility maps were produced for each of the three methods. Susceptibility maps were verified and compared using the area under the curve (AUC) method. The success rate curve demonstrated that the AUC for the IV, WofE, and CF methods was 88.02, 87.56, and 89.04%, respectively, and the prediction rate curve showed that the AUC was 86.24, 86.34, and 87.44%, respectively. Furthermore, results showed that CF method had the highest accuracy in comparison with other methods. Generally, the three methods showed reasonable accuracy in landslide susceptibility mapping. Results of this study can serve as guidelines to managers and policy makers regarding the prevention and mitigation of landslide hazards.

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Section: Study Areamentioning

confidence: 99%

Predictive modeling of landslide hazards in Wen County, northwestern China based on information value, weights-of-evidence, and certainty factor

Wang

Guo

et al. 2019

Geomatics, Natural Hazards and Risk

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“…Values of q > 5.0 L/(sÁm) indicate wells with a superior ability to supply water. Where boreholes did not conform to the 91 mm "standard" diameter, the data were corrected according to the methodology outlined by Qiao et al (2017).…”

Section: Aquifer Water Pressurementioning

confidence: 99%

Prediction of floor water disasters based on fractal analysis of geologic structure and vulnerability index method for deep coal mining in the Yanzhou mining area

Qiao

Zhang³

et al. 2019

Geomatics, Natural Hazards and Risk

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“…Pit dewatering occurs during the coal mining process, which might lead to dry spring and ecosystem degradation at the regional level. The environmental impacts in arid and semi-arid regions can be more severe if no precautionary measure is taken [3]. The environmental impacts include an imbalance between the demand and supply of water and water quality issues.…”

Section: Introductionmentioning

confidence: 99%

Anthropogenic Effects of Coal Mining on Ecological Resources of the Central Indus Basin, Pakistan

Khan

Akhter

Gabriel

et al. 2020

IJERPH

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Water is essential for life, agriculture, and industrialization; however, a rapid increase in population is constantly causing water scarcity and pollution in Pakistan. Mining activities produce the potential toxic element (PTE) accumulation, which lead to unnatural enrichment, ecological pollution, and environmental degradation. The ecological resources impeded by the PTEs cause serious abnormalities in the population through dermal contact, inhalation, and digestion. Mining induced anthropogenic activities are well-known causes of contamination of ecological resources. The produced effluents have drastic effects by changing the physical, chemical, and biological properties of the concerned resources. The Central Indus Basin is a well-known coal regime, where more than 160 mines are active at present. The samples that were collected from the mine water, groundwater, surface water, and the soil were analyzed by atomic absorption and elemental determination analysis (EDA) for an assessment of their quality and the presence of PTEs. The results were correlated with available quality standards, including the World Health Organization (WHO), National Standard of Drinking Water Quality (NSDWQ), World Wildlife Fund (WWF), and Sediment Quality Guidelines (SQGs). These analyses showed the noticeable anthropogenic concentration of PTEs, like iron, cadmium, sulphur, and copper, which can degrade the quality of resources in the Central Indus Basin and have adverse effects on human health. An excessive amount of acid mine drainage (AMD) draws attention to some suitable active or passive treatments for disposal from mines to avoid degradation of ecological resources in the Central Indus Basin of Pakistan.

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Effects of Coal Mining on Shallow Water Resources in Semiarid Regions: A Case Study in the Shennan Mining Area, Shaanxi, China

Cited by 96 publications

References 10 publications

Predictive modeling of landslide hazards in Wen County, northwestern China based on information value, weights-of-evidence, and certainty factor

Predictive modeling of landslide hazards in Wen County, northwestern China based on information value, weights-of-evidence, and certainty factor

Prediction of floor water disasters based on fractal analysis of geologic structure and vulnerability index method for deep coal mining in the Yanzhou mining area

Anthropogenic Effects of Coal Mining on Ecological Resources of the Central Indus Basin, Pakistan

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