Karst pathways and fluvial pathways control hydrology in shallow fluviokarst basins, and numerical modelling of fluviokarst is seldom reported. In this study, we developed a combined discrete-continuum fluviokarst numerical model by simulating surface river routing, in-stream swallet sources and sinks, epikarst storage and dynamic transfer, matrix bedrock interactions, and closed conduit phreatic flow. We applied the model to the Cane Run-Royal Spring basin in Kentucky, USA. Model evaluation indicated that spring discharge alone inadequately constrained model pathways and uncertainty. Instead multi-objective calibration, integrating riverine discharge and well-head data from multiple locations, assisted in identifying sensitive parameters (p < 0.05). Multi-objectives improved representation of stream-cave connectivity and limited prior knowledge biases of the system but was computationally expensive with 168 h required on a high-performance cluster. Results provided evidence for a mature fluviokarst basin with well-defined fracture-conduit network and phreatic aquifer. Residence times of karst pathways vary by five orders of magnitude, ranging from less than one hour in vertical swallets, 12.7 h in longitudinal conduits, 12.7 days in the vadose zone and epikarst, and 142.7 days in the bedrock matrix. Results suggest arrival of source waters to the subsurface systems is disconnected in time from the springflow response. Model simulations show a dimensionless vertical to longitudinal conveyance ratio helps predict swallets linking the fluvial and karst systems. Transferability of the developed model, and other karst models, is discussed relative to availability of information for karst basins.
|Journal||Journal of Hydrology|
|State||Published - Feb 2021|
Bibliographical noteFunding Information:
We gratefully acknowledge the financial support of this research from the Kentucky Senate Bill 271B Water Quality program and National Science Foundation Awards #1632888 and #1933779. We gratefully acknowledge the Center for Computational Sciences at the University of Kentucky for the support provided during model executions on the supercomputer. We acknowledge the work of Jim Currens and Chuck Taylor in setting up and maintaining the groundwater monitoring network. The thank the comments of three anonymous reviewers and Editor Corradini, and addressing these comments greatly improved the paper.
© 2020 Elsevier B.V.
ASJC Scopus subject areas
- Water Science and Technology