RT journal article
T1 Chlorophyll-a and suspended matter variability in a data-scarce coastal-estuarine ecosystem
A1 Chowdhury, M.M.
A1 Caballero, Isabel
A1 Calle, Ignacio de la
A1 Laiz Alonso, Irene María
A2 Física Aplicada
K1 ENSO
K1 Inter-annual variability
K1 Meghna estuary
K1 Northern Bay of Bengal
K1 Seasonal variability
K1 Water quality
AB Analyzing the variability of chlorophyll-a (Chl-a) and total suspended matter (TSM) in estuarine and coastal environments is crucial for understanding ecosystem health, guiding environmental management decisions, and evaluating climate change impacts. Satellite remote sensing offers a powerful tool for this analysis due to its extensive spatial and temporal coverage. Although several algorithms exist for complex coastal and estuarine waters, long-term datasets such as GlobColor's Ocean Color (OC5) and neural network (NN) algorithms are frequently used for robust variability analysis. This study uses the GlobColor NN algorithm to investigate the seasonal and inter-annual variability of Chl-a and TSM in a data-scare region, namely the Meghna estuary in Bangladesh and its adjacent coastal fringe. The other algorithm (i.e. OC5), while offers the longest time series, cannot be used in this region due to the high number of invalid pixels. Therefore, this study examines different environmental factors (i.e. sea surface temperature (SST), photosynthetically active radiation (PAR), rainfall, zonal (ZWC) and meridional (MWC) wind components, and ocean currents) and climatic indices (i.e., El Niño-Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD)) to understand their influence on the seasonal and inter-annual variability of Chl-a and TSM derived from the GlobColor NN algorithm. Empirical orthogonal function analysis identifies the seasonal signal as dominant in the study region. The seasonal cycle of Chl-a is influenced by factors including MWC, TSM, SST, and rainfall. In contrast, TSM seasonal variations are primarily driven by rainfall and MWC. Post-monsoon Chl-a inter-annual fluctuations are mainly linked to TSM inter-annual variability, with secondary influences from monsoon rainfall and the winter ENSO index. Inter-annual changes in TSM are primarily associated with the winter ENSO index and monsoon rainfall. This research elucidates the primary mechanisms influencing Chl-a and TSM variability in the Meghna estuary and its adjacent coast, thus advancing the understanding of the dynamics in the study region. The information obtained through this study is valuable for scientists, policymakers, and stakeholders involved in the sustainable management of the Meghna estuary and its coastal resources, particularly in the context of climate change.
PB Elsevier
SN 0272-7714
YR 2024
FD 2024
LK http://hdl.handle.net/10498/35787
UL http://hdl.handle.net/10498/35787
LA eng
DS Repositorio Institucional de la Universidad de Cádiz
RD 11-nov-2026