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1 July 2021 Assessing the Spatial and Temporal Relationship between Coastal Runoff and Chlorophyll-a in the Philippines Using Gridded Datasets
Manuel Justin G. Custado, Carlos Primo C. David
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Custado, M.J.G. and David, C.P.C., 2021. Assessing the spatial and temporal relationship between coastal runoff and chlorophyll-a in the Philippines using gridded datasets. Journal of Coastal Research, 37(4), 726–736. Coconut Creek (Florida), ISSN 0749-0208.

Publicly available gridded datasets were used in examining the relationship between long-term temporal patterns in runoff rates and chlorophyll-a within the coastal areas of the Philippines. Temporal plots generated from remotely sensed chlorophyll-a data and runoff from the Global Runoff Reconstruction dataset illustrated variabilities in seasonal patterns across coastal segments and climate types. The linear correlation analysis performed on the datasets revealed a characteristic distribution of negative coefficients within the internal seas of the archipelago and positive coefficients in open coasts and embayments. Riverine-influenced sites with positive correlation coefficients (r = 0.33–0.62, p < 0.00001) were mostly associated with delivery of excess nutrients from land-use activities. The distribution of these coefficients was demonstrated to be affected by the physical nature of the coast. Moreover, seasonal changes in total suspended solids adjacent to a river discharge site were discussed, demonstrating how high sediment load can dampen productivity because of limited light penetration in marine waters. The analysis of publicly available datasets in this study provided assessments that can be used to complement coastal management efforts, particularly in the context of increasing anthropogenic stress and climate change.

©Coastal Education and Research Foundation, Inc. 2021
Manuel Justin G. Custado and Carlos Primo C. David "Assessing the Spatial and Temporal Relationship between Coastal Runoff and Chlorophyll-a in the Philippines Using Gridded Datasets," Journal of Coastal Research 37(4), 726-736, (1 July 2021).
Received: 14 September 2020; Accepted: 12 January 2021; Published: 1 July 2021
remote sensing.
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