Modeling the usefulness of spatial correlation analysis on karst systems.

Area of Science:

• Hydrogeology
• Environmental Science
• Geophysics

Background:

• Karst aquifer systems are vital water sources, increasingly threatened by urban development.
• Understanding spatial variations in aquifer properties, particularly recharge distribution, is critical for effective water management.
• Traditional methods often lack the resolution to capture complex spatial heterogeneity in karst systems.

Purpose of the Study:

• To develop and demonstrate a method for spatially characterizing recharge distribution in karst aquifers.
• To utilize cross-correlation analysis with spatially varying precipitation data for inferring recharge locations.
• To expand upon numerical groundwater modeling experiments by incorporating spatially variable parameters.

Main Methods:

• Cross-correlation analysis of field data (precipitation and spring discharge).
• Numerical groundwater modeling using MODFLOW with spatially varying parameters.
• Application of methods to conduit-controlled, matrix-controlled, and mixed karst systems.
• Utilizing multiple precipitation time series inputs.

Main Results:

• Spatially varying aquifer parameters can be inferred from the cross-correlation of precipitation and spring discharge data.
• The cross-correlation analysis effectively characterizes spatial recharge distribution in karst aquifers.
• Numerical simulations using parameters from the Barton Springs Edwards Aquifer validated the inference of spatial variability.

Conclusions:

• Cross-correlation analysis is a viable tool for understanding spatial heterogeneity in karst aquifers.
• The developed method provides a means to spatially characterize recharge, aiding in water resource management.
• Field study at Barton Springs demonstrates the practical application of these techniques.