Simulation study of groundwater flow and solute transport processes in karst underground rivers based on GMS
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摘要: 文章针对遵义市龙洞地下河系统，采用地下水模拟软件GMS（Groundwater Modeling System）构建数值模型。通过构建大渗透系数K概化岩溶地下河的水流特性，旨在通过较少的参数达成较高的模拟效率；利用2022—2023年地下河出口流量数据进行模型识别和验证，确保模拟结果的可靠性；之后通过示踪试验比较模拟与观测数据，揭示当前溶质运移模拟中存在的时间和空间尺度误差，尤其用大渗透系数达西流表征岩溶地下河特性的局限性。结果表明GMS在模拟岩溶地下水流动方面表现出较好的一致性，但在溶质运移模拟方面的精度有待提高，特别是在渗透系数大(
9000 m·d−1)的情况下，预测结果与实际观测存在一定偏差。通过调整模型渗透系数和设置缓冲带，改善模拟精度，并阐明其对溶质运移范围和速度的显著影响，表明参数优化是提高模型预测准确度的关键。提出针对岩溶地下水模拟的改进措施，包括优化模型的参数设置、引入更复杂的水动力学模型（如EPM、DC和CDC模型）以及提高模型在非达西流动条件下的应用能力。未来应继续探索模型参数的最优化，并通过更多实地验证来提高模型的预测能力和适用性，以期为岩溶区水资源管理和保护提供科学的决策支持。Abstract:As the demand for the development and protection of groundwater resources in karst regions increases, accurately simulating the flow and solute transport characteristics of these waters becomes crucial. This study focuses on the Longdong underground river system in Zunyi City to construct a numercial model, utilizing the Groundwater Modeling System (GMS). By conceptualizing the water flow characteristics of the karst underground river with a high hydraulic conductivity coefficient (K), this study is aimed to achieve high simulation efficiency with fewer parameters. This approach is particularly advantageous in karst areas, where traditional modeling techniques may struggle to capture the complex interactions between water flow and geological features. Given the unique geological structures, karst conduits, and fractures present in these regions, a sophisticated model is necessary for proper conceptualization. The model considers the distinct heterogeneity and anisotropy of karst aquifers, with a particular focus on the complex flow patterns characteristic of conduit-dominated flow. Karst aquifers are known for their irregular and often unpredictable flow paths, which can significantly influence the movement of both water and solutes. This study underscores the importance of understanding these flow patterns, as they are critical for effective water resource management and pollution control in karst environments. To ensure the reliability of the simulation results, model identification and validation were conducted with the use of discharge data from the underground river's outlet from 2022 to 2023. This validation process is essential, as it not only confirms the model's accuracy but also enhances the credibility of its predictive capabilities for future scenarios. By utilizing measured data, the study improves the model's reliability, making it a valuable tool for researchers and pollution analysts. Subsequently, tracer tests were conducted to compare simulated and observed data, revealing temporal and spatial scale errors present in current solute transport simulations, particularly highlighting the limitations of using high hydraulic conductivity Darcy flow to characterize karst underground rivers. Tracer tests are vital in hydrological studies, as they provide insights into the movements of solutes within aquifers, enabling researchers to effectively assess of their models. The discrepancies observed in this study highlight the challenges faced in accurately modeling solute transport in environments with high hydraulic conductivity, where traditional assumptions may no longer hold true. This underscores the need for continuous refinement of modeling techniques to better align with the dynamic nature of karst systems. The findings indicate that GMS demonstrates good consistency in simulating karst groundwater flow; however, there is a need to enhance the accuracy of solute transport simulations, especially under high hydraulic conductivity ( 9000 m/d), where deviations between predicted results and actual observations were noted. These discrepancies emphasize the challenges of accurately modeling solute transport under high hydraulic conductivity conditions, suggesting that reliance on high hydraulic conductivity values may lead to oversimplifications that inadequately represent the complexities of solute movement in karst systems. By adjusting the hydraulic conductivity within the model and implementing buffer zones, simulation accuracy was improved, highlighting the significant impact on the range and velocity of solute transport. This indicates that parameter optimization is key to enhancing the predictive accuracy of the model. The introduction of buffer zones also underscores their potential to mitigate scale-dependent errors, providing a novel approach for managing uncertainty in karst system modeling. This innovative method not only enhances the reliability of the model but also serves as a transitional area that helps to smooth discrepancies between modeled and observed data, thereby facilitating model convergence.Finally, this study proposes several improvements for karst groundwater simulations, including optimizing model parameter settings, incorporating more complex hydrodynamic models (such as EPM, DC, and CDC models), and increasing the model's applicability under non-Darcy flow conditions. Furthermore, the study advocates the integration of other models to better represent the interactions between karst conduits and the surrounding matrix, which could lead to more accurate predictions of both flow and solute transport in complex karst terrains. Future research should prioritize the continued optimization of model parameters and enhance the model's predictive accuracy and applicability through extensive field validation. This will provide robust scientific support for decision-making in the management and conservation of water resources in karst regions. In summary, the development of more refined models to improve the resolution of both macroscopic conduit networks and microscopic fracture systems is essential for advancing karst hydrogeological research. -
Key words:
- GMS /
- groundwater /
- numerical simulation /
- karst conduit
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图 1 遵义市龙洞地下河岩溶流域交通位置与水文地质图
Figure 1. Traffic location and hydrogeological map of the karst basin of the Longdong underground river in Zunyi City
图 2 龙洞地下河系统污染成因模式示意图
Figure 2. Diagram of the pollution genesis model for the Longdong underground river system
图 6 2022—2023降雨蒸发分布图
Figure 6. Distribution of precipitation and evaporation from 2022 to 2023
图 10 龙洞地下河系统等水位线及流场图
Figure 10. Contour map of water levels and flow field of the Longdong underground river system
图 14 龙洞地下河出口示踪曲线对比结果
Figure 14. Comparison of the tracer curves at the outlet of Longdong underground river
图 15 不同出口概化的污染物运移距离对比图
Figure 15. Comparison of pollutant migration distances for different outlet generalizations
图 17 不同渗透系数下污染物运移情况示意图
Figure 17. Schematic diagram of pollutant transport under different permeability coefficients
表 1 降雨入渗系数分区表
Table 1. Zoning of rainfall infiltration coefficient
分区依据 降雨入渗系数 分区面积/km2 岩溶 0.50 0.419 有水落水洞 0.65 0.297 落水洞 0.60 0.901 岩溶裂隙 0.25 0.233 山顶 0.2 0.373 河流 0.15 0.116 
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