چكيده لاتين :
Data monitoring is important in the study and analysis of hydrological behaviors of karstic
systems. Monitoring shows the various regimes of groundwater flow (laminar or turbulent), depletion,
filling, filtration and karstification degree of karst aquifers. In recent years, analyses of these data had
considerable advances using stochastic time series analyses. An important problem related to these
analyses is the constraint of financial and technical human support. If we can increase the time intervals,
the costs are lowered and development of new monitoring networks will be possible. Tn this research, the
effect of monitoring time intervals on the results of time series analysis and calculated hydrologic delay
times are studied, using bivariate analyses in spectral domain. The first (shorter) and the second (longer)
delay times are related to the flow of groundwater through the larger and smaller fractures of the karstic
system, respectively. Daily groundwater level data of three piezometers and the discharge of a spring in
the Maharlu karst basin in Iran (52°12יto 53°28יE and 29°1י to 30°6יN) were acquired and then six
different time series having different time intervals (1, 3, 7, 10, 14 and 30 days) were extracted and
analyzed. The results show that the variation of the computed stochastic parameters with increasing time
intervals is unpredictable, but the variation of time (period) corresponding to the frequency at the peak of
amplitude function (curve) shows a linear and predictable relationship, which is unique for every kind of
karstic aqui fer having different degrees of karstification
