In order to accurately know the progress in frontier technologies and research hotspots in environmental monitoring and protection during deep-sea mining, after the patents and academic literature from January 1, 2005 to April 14, 2025 in the filed of deep-sea mining were retrieved with IncoPat and Web of Science, a statistical analysis was performed with bibliometric methods for542 published patents and 469 academic literature, and then the development trend in this field was also discussed. It is shown that a synchronous increase in both patents and academic literature highlights the support of basic research for technological innovation. By formulating corresponding policies and through institutional collaboration, China hasshifted its place from following others to keeping pace and even leading the pack in theoretical research. China has also put emphasis on the technologies of environmental monitoring and protection in its scientific research on deep-sea mining, and established a technical system and theoretical framework with in situ observation technologies for environmental impacts during deep-sea mining at the core. As a result, the research perspective has shifted toward understanding of complex system mechanisms. In the future, the environmental monitoring and protection system for deep-sea mining will be composed of four core modules, including environmental monitoring, environmental assessment, environmental management and environmental protection, and form an ecological risk supervision and management framework through the whole mining process, which will also becontinuallyupdated.

Several pieces of hard paper with different numbers, dip angles and widths were embedded into specimens to simulate structure of closed joint in rock masses and prepare rock mass models with different joints. Effect of joints on blast-induced failure characteristics of rock mass was analyzed with a high-speed camera and a 3D laser scanner, so as to explore the rules of crack propagation and fragment size distribution during rock blast. It is found that joints can disperse blasting energy and hinder crack penetration, leading to a decrease in the average size of blast-induced fragments as the number of joints increases. Wider joints can make diffraction and reflection of stress waves much more complicated, intensify energy dissipation, and also hinder crack propagation; while joints with small width are prone to make blast-induced fragments smaller in size. The interaction between joint dip angle and the propagation direction of the blast stress wave can significantly affect the crack propagation mode, and excessively large dip angles can easily hinder stress wave propagation.

As for backfill slurry transported through reducing bends, the effect of bend angle, inlet flow velocity, mass fraction and average particle size of slurry, mass flow rate, particle shape factor and particle impact angle on the erosive wear of reducing bends were analyzed with Fluent software. The results show that the inlet flow velocity of slurry exerts the most significant impact on the erosion-prone areas of pipeline. With the inlet flow velocity up from 0.8 m/s to 2.0 m/s, the erosion rate in the erosion-prone areas of the pipeline surges approximately 43 times. The average particle size of the slurry ranks second in terms of its impact on the pipeline's erosion-prone areas, while the bend angle and particle impact angle have relatively minor effects. It is found that the erosion rate in pipeline is related to the kinetic energy of slurry; the greater the kinetic energy of the slurry, the more severe the erosion. The erosive wear locations of pipeline are primarily distributed at the inlet, the inner and outer wall surfaces of the bend, and reducing section and the straight section to the elbow, with the connection between the reducing section and the outlet section worn most severely.

As for rainfall-induced landslides in Mayang, Yuanling and Luxi counties within the red-bed region of the Yuanma Basin in Hunan Province, a correlation between landslides and rainfall were analyzed. Based on the E-D threshold model, the daily rainfall (R) was introduced as a third indicator to construct an E-D-R threshold model, thereby rainfall thresholds were determined for the Yuanma Basin. The study area was divided into warning units with the Thiessen Polygon method, enabling a county-level, unit-based graded warning response. The results show that the period from four days before a landslide to the day of the landslide represents the critical rainfall period for inducing landslides in the Yuanma Basin, and it is deemed appropriate for the effectiveness coefficient (α) of the rainfall to be 0.5. Compared to the two-dimensional E-D threshold model, the three-dimensional E-D-R threshold model demonstrates higher precision and offers greater accuracy and reliability in landslide risk assessment. The grid-based and refined division of warning units not only enhances the refined management and control capabilities of meteorological warnings for landslide disasters, but also facilitates unit-specific differentiated warnings in future forecasting by integrating predicted rainfall and rain information.

As for the slope collapse at bench merging section in an open-pit mine, engineering geological analysis, analysis with stereographic projection and mechanical analysis were employed to comprehensively explore the main factors inducing slope collapse. Based on the causes and instability characteristics of slope collapse, a management scheme was proposed and thoroughly demonstrated. The results show that the collapse of bench slope occurs under the combined effects of rainfall infiltration and excavation at bench merging section, and induced effects of rock mass properties and weathering fracture surfaces. A management scheme of “gravity retaining wall foot pressure + gravel soil backfilling + shotcrete and rock bolt support” was proposed. The overall stability coefficient of the slope after management is 1.39, meeting the safety standard requirements.

Wavelet analysis was performed for the collected pressure signals of gas-liquid two-phase flow in a vertical pipe in an air lift test. The optimal wavelet basis functions were determined by improving the signal-to-noise ratio (SNR). The range of decomposition levels was determined based on changes in energy of detail coefficients, and optimal decomposition levels were determined by the entropy weight method together with SNR, root mean square error and smoothness. After denoise with wavelet thresholding, three-level decomposition of signal was performed with the wavelet packet method, and then flow patterns were identified for gas-liquidtwo-phase flow with the energy ratio in the 1st and 2nd frequency bands and entropy values as feature vectors. The flow pattern recognition based on 389 sets of pressure signals shows that the extraction feature vector combined with random subspace decision tree can efficiently identify and classify gas-liquid two-phase flow patterns, and the overall mean recognition rate is up to 98.08% by adopting the improved wavelet thresholding.