MA Y L, CHEN C, ZHANG X J，et al．Research advances and development trends in rainfall monitoring technologies for tailings ponds［J］.Journal of Henan Polytechnic University( Natural Science)，doi:10.16186/j.cnki.1673-9787. 2025030067

doi: 10.16186/j.cnki.1673-9787.2023050067

Received：2025-03-29

Revised：2025-05-19

Online：2025-06-12

Research advances and development trends in rainfall monitoring technologies for tailings ponds

Ma Yongli^{1, 2}, Chen Cheng^{1, 2}, Zhang Xiaojun³, Liu Yanzhi⁴, Guo Qingwei^{1, 2}, Zhang Xiaobo^{1, 2}

(1.School of Infrastructure Engineering, Nanchang University, Nanchang 330031, Jiangxi, China; 2. Jiangxi Provincial Key Laboratory of Hydraulic Geotechnical Engineering Safety, Nanchang 330031, Jiangxi, China; 3. Jiangxi Academy of Emergency Management Science, Nanchang 330000, Jiangxi, China; 4. Jiangxi Duchang Jinding Tungsten & Molybdenum Mining Co., Ltd., Jiujiang 332611, Jiangxi, China)

Abstract: [Objective] Rainfall monitoring constitutes a critical component of tailings pond safety prevention and control systems, as its accuracy directly affects the assessment of major risks such as phreatic line elevation and seepage-induced instability of dam structures. Targeting the complex terrain of valley-type tailings ponds and the significant spatiotemporal heterogeneity of localized rainfall, this study systematically reviews the developmental trajectory of rainfall monitoring technologies. The research aims to establish a distributed precision monitoring technology system tailored to complex topographic conditions, thereby enhancing the safety management of tailings ponds throughout their lifecycle. [Methods] Utilizing bibliometric analysis and case study methodologies, this paper systematically examines the evolution of rainfall monitoring technologies for tailings ponds both domestically and internationally. The measurement principles and engineering applicability of three mainstream techniques—ground-based rain gauge networks, weather radar detection, and satellite remote sensing inversion—are critically analyzed. Comparative evaluations reveal common limitations in valley terrain applications, including extensive monitoring blind spots, low spatiotemporal resolution, and poor inversion accuracy. [Results] An innovative distributed precision monitoring technology system for valley-type tailings ponds is proposed: (1) A piezoelectric rain gauge is developed to address the technical bottlenecks of traditional tipping-bucket sensors, such as susceptibility to clogging and discontinuous data acquisition; (2) A boundary-constrained optimization model for sensor network deployment is established, achieving dynamic spatial alignment of monitoring points with rainfall intensity gradients in complex terrains; (3) An edge computing-integrated intelligent gateway is designed to construct an adaptive data acquisition and transmission mechanism responsive to rainfall intensity variations. [Conclusion] This study not only systematically elucidates the developmental trends in tailings pond rainfall monitoring technologies but also constructs a practical technical framework. With the integration of emerging technologies such as multi-source sensor fusion, deep learning algorithms, and digital twin platforms, future systems will evolve into a holistic ecosystem encompassing real-time monitoring, intelligent analysis, and dynamic early warning capabilities. The findings provide critical theoretical and technical support for advancing risk prevention strategies and promoting the construction of smart mining infrastructures.

Key words: tailings ponds; rainfall monitoring; piezoelectric rain gauge; distributed; edge computing

CLC: