In many places throughout the world, drinking water is frequently contaminated by turbidity. Such turbidity, however, as representative of particle transport, can be used as to trace certain features of particle transport properties. In order to investigate the relation between particle and dissolved species transport and hydrodynamics in karst systems, correlation and spectral analyses were performed on time series of rainfall (input signal), and water level, specific conductance, and turbidity (output signals) at a karst spring system in the chalk aquifer of the lower Seine valley, France. This system is composed of a spring connected to a sinkhole on the chalk plateau where a small creek enters the subsurface. The autocorrelation functions for water level and turbidity showed a short memory effect, demonstrating the short duration of the influence of flood events on these two parameters, whereas specific conductance (representing less-mineralized storm-derived water) had a much longer memory effect. These results were interpreted as reflecting the rapid reactivity of the spring to rain events, with storage of water in the fissured chalk explaining the longer memory effect for specific conductance than for particles. Energy spectra computed by fast Fourier transform of autocorrelation functions showed a strong structure in the output signals, whereas the input signal (rainfall) was random, thus allowing assessment and comparison of system behaviour regarding dissolved and solid transport, as well as hydraulics. Cross-correlation functions (which allow an assessment of impulse response functions) confirmed the low inertia of the system for water level and turbidity and the much higher inertia for specific conductance. In addition to the main peak, two secondary peaks in the cross-correlation functions suggest the existence of additional flowpaths that might involve the contribution of other point-source recharge and/or delayed infiltration through the clayey surficial formation and solution pipes, which could act as epikarst. Analysis using continuous wavelet spectra allowed a better investigation of the rainfall signal structure and highlighted a strong relationship between turbidity and rainfall, which could not be deduced from the energy spectra. Specific spectral components in water level were isolated and a time-domain reconstruction using inverse wavelet transform allowed separation of quick-flow and slow-flow components.