Combining Experimental Methods and Modeling toQuantify the Complex Recharge Behavior ofKarst Aquifers

Files

Link to Full Text

Download Full Text

Publication Date

2-1-2019

Publication Title

Water Resources Research

Volume Number

55

Issue Number

2

Abstract

Integration of the abundant information derived from different sources, characterizingtechniques and modeling methodologies, is crucial for extending our knowledge of karst aquifers andtheir available water resources. In this work, a numerically based approach derived from an improvedversion of the lumped VarKarst model is proposed, which jointly considers spring discharge and dye testresults in calibration routine, to assess independently the contribution of the allogenic and autogeniccomponents to the total recharge of a complex karst system with proved duality in its rechargemechanisms. A newly developed parameter estimation procedure based on rather soft performance rules isemployed to confine the uncertainty of the water budget previously obtained with two other independentmethods (Soil Water Balance and APLIS). Unlike other methodologies that lead to semiquantitativeestimations of input sources, results from our approach display reliable ranges of calibrated values forrecharge rate, recharge area, and, to a lesser extent, for water runoff infiltration coming from thestreamflow. The integration of all these quantitative results with data (qualitative) previously derived fromother experimental methodologies has meant a significant advance in understanding the behavior of thepilot system, allowing a more realistic and robust conceptual model to be developed. We conclude byemphasizing that a continuous transfer of improvements from conceptual to numerical modelingapproaches, and vice versa, is necessary to enhance knowledge of carbonate aquifer functioning andultimately achieve better evaluation and management of water resources. During this process, frequentmutual evaluation between the modeling approaches must be performed.

Document Type

Article

Digital Object Identifier (DOI)

http://dx.doi.org/10.1029/2017WR021819

Share

 
COinS