Jiameng Chen
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Research Interests
Jiameng Chen has a total of 9 co-authors. Here are the top co-authors by number of shared publications:
- Changhong Hou
College of Geoscience and Surveying Engineering, China University of Mining and Technology (Beijing), Beijing 100083, China
1 shared publication - Cheng Luo
College of Geoscience and Surveying Engineering, China University of Mining and Technology (Beijing), Beijing 100083, China
1 shared publication - Jiahui Yu
College of Geoscience and Surveying Engineering, China University of Mining and Technology (Beijing), Beijing 100083, China
1 shared publication - Jie Dong
Qingdao Key Laboratory of Groundwater Resources Protection and Rehabilitation, Qingdao 266101, China
1 shared publication - Liu Yang
College of Geoscience and Surveying Engineering, China University of Mining and Technology (Beijing), Beijing 100083, China
1 shared publication - Ming Gao
College of Geoscience and Surveying Engineering, China University of Mining and Technology (Beijing), Beijing 100083, China
1 shared publication
Latest Publications
- Open Access
Effects of Climate Variables and Human Activities on Groundwater Level Fluctuations in Unconsolidated Sedimentary Aquifers: A Data-Driven Approach
Groundwater level (GWL) in unconfined aquifers is highly susceptible to climate variables and human activities, exhibiting nonlinear fluctuations; these can further contribute to or exacerbate environmental hazards, such as land subsidence. Understanding the relationship between GWL changes and external conditions is essential for effective groundwater resource management and ecological protection. However, this relationship remains unclear and variable. This study systematically analyzes the correlations between climate and human factors and GWLs, using data from monitoring stations in the unconsolidated sedimentary aquifers of Beijing, China. It evaluates the importance of influencing factors on GWL simulation accuracy and tests how different inputs affect simulation performance. The results indicate that human factors are more strongly correlated with GWLs, yet climate factors hold higher importance scores. In GWL simulations, different input variables yield varying accuracy, with the inclusion of precipitation notably decreasing simulation precision because of its lagged or indirect effects on groundwater levels. The variation in accuracy across monitoring stations further suggests that the primary differences may stem from the GWL data itself. These findings underscore the need for high-resolution, localized data and tailored input selection to improve GWL projections and inform adaptive water-resource strategies under changing climatic and anthropogenic pressures.
Open AccessEffects of Climate Variables and Human Activities on Groundwater Level Fluctuations in Unconsolidated Sedimentary Aquifers: A Data-Driven Approach
Groundwater level (GWL) in unconfined aquifers is highly susceptible to climate variables and human activities, exhibiting nonlinear fluctuations; these can further contribute to or exacerbate environmental hazards, such as land subsidence. Understanding the relationship between GWL changes and external conditions is essential for effective groundwater resource management and ecological protection. However, this relationship remains unclear and variable. This study systematically analyzes the correlations between climate and human factors and GWLs, using data from monitoring stations in the unconsolidated sedimentary aquifers of Beijing, China. It evaluates the importance of influencing factors on GWL simulation accuracy and tests how different inputs affect simulation performance. The results indicate that human factors are more strongly correlated with GWLs, yet climate factors hold higher importance scores. In GWL simulations, different input variables yield varying accuracy, with the inclusion of precipitation notably decreasing simulation precision because of its lagged or indirect effects on groundwater levels. The variation in accuracy across monitoring stations further suggests that the primary differences may stem from the GWL data itself. These findings underscore the need for high-resolution, localized data and tailored input selection to improve GWL projections and inform adaptive water-resource strategies under changing climatic and anthropogenic pressures.