Use of ordinary Kriging algorithm and wavelet analysis to understanding the turbidity behavior in an Amazon floodplain

The objective of this paper is to study the turbidity behavior in an Amazon Floodplain Lake. Observations of turbidity provide quantitative information about water quality conditions. However, the number of available in situ measurements of water quality characteristics is usually limited, especially temporal series variables and synoptic coverage of extensive water body. In order to contribute to the study of turbidity we present two approaches: (i) the first is based on wavelet analysis of a turbidity time series measured by an automatic monitoring system; (ii) the second is based on spatially distributed turbidity samples analized by Ordinary Kriging algorithm. The main results are: the space/time turbidity variability is related to Amazon river flood pulse in the floodplain; during the rising and receding water stages, the water exchange between Amazon river and floodplain is the major driven force in turbidity variability; during the high water level, the lake bathymetry controls turbidity variability; and during the low water level, the wind intensity and lake morphometry are the main causes of turbidity variability. The joint use of temporal and spatial data showed a great potential for understanding the turbidity behavior in a complex aquatic system, like the Amazon floodplain.