Groundwater Circulation and Origin of Salinity in a Multi-aquifer System: The Gohar-Zamin Mining Area, Iran

Gharaat, Mohammad Javad; Assari, Amin; Rezanezhad, Fereidoun

doi:10.1007/s10230-022-00902-6

Cited by 5 publications

(3 citation statements)

References 55 publications

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“…This method involves analyzing major ions and comprehensive water quality indicators to determine the water quality types of the aquifer and the inrush water. Major ions such as Ca 2+ , K + , Na + , SO 4 2− , HCO 3 − , Mg 2+ , Cl − , and CO 3 2− are examined, along with comprehensive indicators like dissolved oxygen, alkalinity, acidity, pH value, and mineralization.…”

Section: Traditional Techniques For Water Source Discriminationmentioning

confidence: 99%

“…Water inrush incidents pose a formidable peril, imperiling both the safety of miners and the efficiency of coal production [1]. The specter of water inrush accidents looms large over the mining safety landscape worldwide, particularly in nations with robust coal industries, such as China, the United States, India, Iran and Australia [2][3][4]. Despite stringent regulatory measures, these catastrophes have tragically exacted a heavy toll in terms of lives lost and properties devastated over the years [5].…”

Section: Introductionmentioning

confidence: 99%

“…The conventional hydrochemical method serves as the primary means of analyzing the primary ion content, which includes indicators such as Ca 2+ , K + , Na + , SO 4 2− , HCO − , Mg 2+ , Cl − , CO 3 2− , dissolved oxygen, alkalinity, acidity, pH value, and mineralization degree. This method plays a crucial role in determining the water quality classification of both the aquifer and the water influx [7][8][9][10][11][12][13][14][15][16][17][18][19][20][21][22][23].…”

Section: Introductionmentioning

confidence: 99%

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Discrimination Methods of Mine Inrush Water Source

Dong,

Zhang

2023

Water

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Ensuring mining safety and efficiency relies heavily on identifying the source of mine water inrush. This review article aims to provide a comprehensive overview of standard methods used to pinpoint the origin of mine water inrush, highlighting the development and progress in the research of discrimination methods. These methods are systematically classified into various categories, encompassing hydrochemistry examination, water level and temperature analysis, geostatistical approaches, machine learning and deep learning methods, as well as the utilization of other analytical techniques. The review not only presents a quantitative and visual analysis of the theoretical methods proposed by scholars but also emphasizes their strengths, weaknesses, and applicability to various mining operations. Furthermore, it explores the increasing utilization of artificial neural networks and machine learning algorithms in source discrimination models, indicating the advancement in this area of research. To further advance the field, specific examples of these methods and their effectiveness in identifying the source of mine water inrush are provided, aiming to stimulate further research. The article also offers detailed recommendations for future research directions and emerging trends, underlining the importance of comprehensive multidisciplinary and multi-method analysis. It suggests exploring emerging technologies such as the Internet of Things (IoT) and cloud computing, while emphasizing the need to develop more accurate and reliable models for source identification. The fusion of artificial intelligence (AI), heightened computational capabilities, online programming, and intelligent data collection systems presents the prospect of transforming the way industries respond to these critical events. By providing a comprehensive overview, analyzing the effectiveness of existing methods, and proposing future research directions, this review aims to contribute to the continuous development and progress of discrimination methods for mine water inrush incidents. Ultimately, it seeks to enhance mining safety and efficiency by facilitating the prompt and accurate identification of the sources of mine water inrush.

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Section: Traditional Techniques For Water Source Discriminationmentioning

confidence: 99%