With the substantial increase in karst groundwater pollution, the pollution caused by heavy metal migration has become one of the hottest topics. The migration characteristics of heavy metals in karst groundwater are closely related to the geological environment in which they are found. Therefore, this review focuses on the migration characteristics of heavy metals in karst groundwater in southern and northern China and highlights the effect of different environmental contexts such as atmosphere (precipitation), vegetation, soil, rock, and aquifers on the behavior of heavy metals. It also summarizes existing research methods on heavy metal migration in karst groundwater. Meanwhile, current advances and the future perspectives on karst groundwater heavy metal migration will be presented. It is hoped that this review may shed light on the study of heavy metal migration in karst areas.

In this study, 24 surface water samples were collected from the main trunk/tributary of the Lijiang River during the wet season (April) and the dry season (December) in 2021. The total concentration of 11 heavy metal(loid)s (Al, Cu, Pb, Zn, Cr, Ni, Co, Cd, Mn, As, and Hg) was determined to investigate their physicochemical properties and spatial-temporal distribution characteristics. The heavy metal evaluation index (HEI) and the positive matrix factorization (PMF) model were employed to evaluate water quality and to reveal quantitatively identified pollution sources for further investigation to obtain a health risk assessment using the hazard index (HI) and carcinogenic risk (CR) of various pollution sources. The mean concentrations of heavy metal(loid)s in surface water in the wet and dry seasons were ranked as: Al > Mn > Zn > Ni > Cd > Cr > Cu > As >Hg = Pb > Co, with the mean concentration of Hg being higher than the national Class II surface water environmental quality standard (GB3838-2002). In terms of time scale, the concentration of most heavy metal(loid)s was higher in the wet season; most heavy metal(loid)s were distributed mainly in the midstream area. HEI index indicated that the main water quality status was “slightly affected” in the study area. Five potential sources of pollution were obtained from the PMF model, including industrial activities, traffic sources, agricultural activities, domestic waste emissions, and natural resources. The source-oriented risk assessment indicated that the largest contributions of HI and CR were agricultural sources in the Lijiang River. This study provides a “target” for the precise control of pollution sources, which has a broad impact on improving the fine management of the water environment in the basin.

Xiahe County, in the northwestern Gannan Tibetan Autonomous Prefecture of Gansu Province, faces recurrent geological hazards—including landslides and debris flows. Geological hazards in highly vegetated regions pose severe threats to ecological balance, human settlements, and socio-economic sustainability, hindering the achievement of sustainable development goals (SDGs). Due to the significant topographic relief and high vegetation coverage in this region, traditional manual ground-based surveys face substantial challenges in the investigation and identification of geological hazards, necessitating the adoption of advanced monitoring and identification techniques. This study employs a comprehensive approach integrating optical remote sensing, interferometric synthetic aperture radar (InSAR), and unmanned aerial vehicle (UAV) photogrammetry to investigate and identify geological hazards in the eastern part of Xiahe County, exploring the application capabilities and effectiveness of multisource remote sensing techniques in hazard identification. The results indicate that this study has shortened the time required for on-site investigations by improving the efficiency of disaster identification while also providing comprehensive, multi-angle, and high-precision remote sensing outcomes. These achievements offer robust support for sustainable disaster management and land use planning in ecologically fragile regions. Optical remote sensing, InSAR, and UAV photogrammetry each possess unique advantages and application scopes, but single-technique approaches are insufficient to fully address potential hazard identification. Developing a comprehensive investigation and identification framework that integrates and complements the strengths of multisource technologies has proven to be an effective pathway for the rapid investigation, identification, and evaluation of geological hazards. These results contribute to regional sustainability by enabling targeted risk mitigation, minimizing disaster-induced ecological and economic losses, and enhancing the resilience of vulnerable communities.

A landscape ecological risk model was constructed to evaluate the landscape ecological risk pertaining to Lanzhou City based on the land use and land cover (LULC) changes obtained using remote sensing data for the years 2000, 2010, and 2020 covering the duration 2010–2020. Results show that during 2010–2020, the LULC types in Lanzhou City mainly comprised of cropland, grassland, and construction land. In terms of LULC changes in Lanzhou City the trend shows a decrease in cropland and increase in construction land with an increase in the fragmentation and separation of cropland, grassland, and shrubland, which is pronounced for cropland and shrubland. The spatial distribution pattern of ecological risk shows very high and very low levels of risk in the main urban area in the south and in the northwest of the city, respectively. From 2010 to 2020, the ecological risk level of the landscape shows a gradual increase with evidence for significant changes. The results of the study provide a scientific basis for the optimization of the landscape pattern, rational utilization and development of land resources in Lanzhou City, and lay a solid foundation for the formulation of ecological risk control measures.