Combining Experimental Methods and Modeling to Quantify the Complex Recharge Behavior of Karst Aquifers. - Mudarra-Martínez, Matías; Hartmann, A.; Andreo-Navarro, Bartolomé (American Geophysical Union, 2019)
Integration of the abundant information derived from different sources, characterizing techniques and modeling methodologies, is crucial for extending our knowledge of karst aquifers and their available water resources. In this work, a numerically based approach derived from an improved version of the lumped VarKarst model is proposed, which jointly considers spring discharge and dye test results in calibration routine, to assess independently the contribution of the allogenic and autogenic components to the total recharge of a complex karst system with proved duality in its recharge mechanisms. A newly developed parameter estimation procedure based on rather soft performance rules is employed to confine the uncertainty of the water budget previously obtained with two other independent methods (Soil Water Balance and APLIS). Unlike other methodologies that lead to semiquantitative estimations of input sources, results from our approach display reliable ranges of calibrated values for recharge rate, recharge area, and, to a lesser extent, for water runoff infiltration coming from the streamflow. The integration of all these quantitative results with data (qualitative) previously derived from other experimental methodologies has meant a significant advance in understanding the behavior of the pilot system, allowing a more realistic and robust conceptual model to be developed. We conclude by emphasizing that a continuous transfer of improvements from conceptual to numerical modeling approaches, and vice versa, is necessary to enhance knowledge of carbonate aquifer functioning and ultimately achieve better evaluation and management of water resources. During this process, frequent mutual evaluation between the modeling approaches must be performed
Keywords: Acuíferos; Cambios climáticos; Minerales carbonatados; Karst; Water resources; Modelling; Climate change