TITLE:
Understanding Seasonal and Spatial Variation of Water Quality Parameters in Mangrove Estuary of the Nyong River Using Multivariate Analysis (Cameroon Southern Atlantic Coast)
AUTHORS:
Anselme Crépin Mama, Willy Karol Abouga Bodo, Gisele Flodore Youbouni Ghepdeu, Gordon Nwutih Ajonina, Jules Rémi Ngoupayou Ndam
KEYWORDS:
Water Quality Parameters, Nyong Estuary, Principal Component Analysis
JOURNAL NAME:
Open Journal of Marine Science,
Vol.11 No.3,
July
30,
2021
ABSTRACT: To evaluate the actual status of water quality and conclude on the mains source of pollution in the Nyong estuary River, seasonal and spatial variation of water quality parameters was interpreted by multivariate statistical techniques (Principal Component analysis). Nine (09) environmental variables were monitored at four surface stations in the estuary for two seasonal cycles. The fieldwork was conducted from 2018 to 2019 during high tide and low tide for each survey. In situ physical parameters were measured for a total of 64 samples (32 samples for each tide). The laboratory works consisted of some physicochemical analyses and processing of these data by descriptive and multidimensional statistical analyses. Temperature, suspended particle matter, nitrate, nitrite and phosphate change significantly in the estuary with season (p p > 0.05). Principal Component analysis found temperature, salinity, pH, ammonium to be the most important parameters contributing to the fluctuations of surface water quality in the Nyong estuary during the dry seasons whereas suspended particle matter, nitrate, and phosphate are the most important parameters contributing to the fluctuation of surface water quality in the Nyong estuary during the rainy seasons. Based on spatial variation, the Principal Component analysis found that, suspended particle matter, nitrate and phosphate contribute to the fluctuation of surface water quality parameters upstream of the estuary while downstream salinity, pH, and ammonium contribute the most to the fluctuation of surface water quality. This study shows us the usefulness of multivariate statistical techniques used in assessing water quality data sets that would help us in understanding seasonal and spatial variations of water quality parameters to manage estuarine systems.