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Water Resources Research

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Karst aquifers contain significant water reserves in many parts of the world, but development and management of these reserves is difficult because of the complexity of the aquifers. This paper presents a method of characterizing karst aquifers based on the use of single, linear kernel functions. The kernels are identified with a deconvolution technique proposed by Neuman and de Marsily (1976) by using estimated groundwater recharge during isolated storms as the system input and the rapid storm response of spring flow as the system output. Derived kernels for large springs from data for different storms are similar in shape and time to peak. Average kernels derived from spring flow responses for multiple storms differ in shape for different springs but suggest a regularity in the response of individual springs to precipitation. The derived kernel functions presently cannot be validated because of the use of a scaling factor in the moisture balance for the springs. They can be used, however, to predict the storm response of a spring if the total volume of the rapid spring flow response is known.

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