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Long-term environmental time series of continuously collected data are fundamental to identify and classify pulses and determine their role in aquatic systems. This paper presents in situ daily mean chlorophyll-a concentration time series, key information for the current understanding of carbon fluxes in and out of the Amazonian floodplain system. This paper also investigates how seasonal fluctuations in water level affect the relationship between chlorophyll-a concentration and some of its controlling limnological (water level, water surface temperature, pH and turbidity) and meteorological (wind intensity, relative humidity and short wave radiation) variables provided by an automatic monitoring system (Integrated System for Environmental Monitoring-SIMA) deployed at Curai Lake. The data are collected in preprogrammed time interval (1 h) and are transmitted by satellite in quasi-real time for any user in a range of 2500 km from the acquisition point. We used Pearson correlation to determine the quantitative relationship between chlorophyll-a time series and others environmental parameters. Fourier power spectrum analyses were applied to identify periods of high variability in chlorophyll-a time series and wavelet power spectrum analyses helped to characterize their time-frequency structure. To further investigate the relationship between chlorophyll-a and the statistically significant variable highlighted by Pearson’s correlation, the set of time series was submitted to cross wavelet analysis. The time series of chlorophyll-a shows two high peaks (47 μg L−1 and 53.30 μg L−1) of concentration during a year: first during the rising water and second during the low water level. A small peak was observed during the high water level (10 μg L−1). For the most part of rising, high and receding water level, the chlorophyll-a concentration is often low (from 2.20 μg L−1 to 9.10 μg L−1). chlorophyll-a concentration displays periodicities ranging from 260 days, with a coherence of approximately 1 in phase with water level during the rising and low water period. Water level dynamics and turbidity explain 68% of the chlorophyll-a time series variability.