Analysis of karst aquifer spring flows with a gray system decomposition model

Area of Science:

• Hydrogeology
• Environmental Science
• System Dynamics

Background:

• Karst aquifers in North China, covering ~470,000 km², supply major springs but exhibit turbulent flow, challenging conventional groundwater models.
• Limited groundwater data in these karst systems hinders quantitative analysis of flow dynamics and spring discharge.
• Classical Darcy's law-based models are inadequate for the complex, often turbulent, flow regimes prevalent in karst environments.

Purpose of the Study:

• To develop a parsimonious predictive model for karst spring discharge utilizing gray system theory.
• To address the challenge of data scarcity and complex flow conditions in North China's karst aquifers.
• To provide a quantitative tool for understanding and forecasting spring discharge dynamics.

Main Methods:

• Application of gray system theory, which models systems with partial or uncertain characteristics.
• Decomposition of spring discharge time series into long-term trend, periodic variation, and random fluctuation components.
• Simulation of the long-term trend and extraction of other components using the gray system model.

Main Results:

• The developed gray system model effectively simulates karst spring discharge time series.
• Model application to Liulin Springs demonstrates robust performance in predicting discharge patterns.
• Forecasts indicate a probable declining trend in Liulin Springs discharge, accompanied by minor fluctuations.

Conclusions:

• Gray system theory offers a viable approach for modeling and predicting discharge in data-scarce, complex karst systems.
• The developed model provides valuable insights into the future discharge trends of North China's karst springs.
• Findings highlight the need for adaptive water resource management strategies in regions with similar hydrogeological conditions.