Defining the hydrogeological behavior of karst springs through an integrated analysis: a case study in the Berici Mountains area (Vicenza, NE Italy)

Alternative Title

Hydrogeology Journal

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Publication Date

2-14-2020

Volume Number

28

Abstract

Knowledge of the hydraulic and geological properties of karst systems is particularly valuable to hydrogeologists because these systems represent an important source of potable water in many countries. However, the high heterogeneity that characterizes karst systems complicates the definition of karst hydrogeological properties, and their estimation involves complex and expensive techniques. In this study, a workflow for karst spring characterization was used to analyze two springs, Nanto spring and Mossano spring, located in the Berici Mountains (NE Italy). Based on the data derived from 4 years of continuous hourly monitoring of discharge, water temperature and specific electrical conductivity, a hydrogeological conceptual model for the monitored springs was proposed. Flow rate measurements, which combined recession curve, flow duration curve and autocorrelation function techniques, were used to evaluate the spring discharge variability. Changes in spring discharge can be related both to the degree of karstification/permeability and to the size of the karst aquifer. Moreover, combining monitored parameters and rainfall—analyzed by the cross-correlation function and VESPA (Vulnerability Estimator for Spring Protection Areas) index approach—permitted assessment of the spring response to recharge and the behavior of the drainage system. Although the responses to the recharge events were quite similar, the two springs showed some differences in terms of the degree of karstification. In fact, Mossano spring showed a more developed karst system than Nanto spring. Three systems (two karsts and one matrix/fractured) are outlined for Mossano spring, while two systems (one karst and one matrix/fractured) are outlined for Nanto spring.

Keywords

Karst, Statistical analysis, Time series analysis, Conceptual models, Italy

Document Type

Article

Digital Object Identifier (DOI)

https://doi.org/10.1007/s10040-020-02122-0

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