INFLUENCE OF SEA SURFACE TEMPERATURE AND PRECIPITATION ON CHL-A VARIABILITY IN JAKARTA BAY - Marasabessy, Nabila
Jakarta Bay is often observed with algal blooms. Water quality management to prevent adverse impacts on important ecosystems is carried out. Chlorophyll-a (Chl-a) is a phytoplankton indicator that can be used to observe the variation of phytoplankton in an aquatic environment. This research seeks to understand the spatial and temporal variability of Chl-a in Jakarta Bay as well as the factors that influence it. This research observed sea surface temperature (SST), rainfall, and land use as factors. The data being utilized is a level 3 Aqua-MODIS satellite image for monthly and climatological Chl-a and SST parameters. The concentration distribution of Chl-a and SPL over time is mapped using satellite image data. Chl-a, SPL, and rainfall time series include monthly, climatological, and anomalous information. Predictions of potential nutrient emissions are generated based on domestic, agricultural, livestock, and agricultural land use data. The spatial and temporal variability of the data is then analyzed descriptively, seasonally, and interannually. To improve data signals, analysis of empirical orthogonal functions (EOF) are performed. The result is that there is no indication of upwelling, so it is assumed that the availability of nutrients comes from the land. In the watershed of the study site, it is known that there has been a two-fold increase in the prediction of potential nutrient emissions between 2002 and 2021. It suggests that coastal areas have greater concentrations of Chl-a. The study examines the spatial variability of climatological eutrophic status, with a focus on monthly variations and the subsequent analysis of land features. The occurrence of eutrophic status coincides with reports of algal blooms that have had a negative impact. It suggests that SST fluctuation patterns are influenced by sunlight radiation, which is the main source of phytoplankton energy, characterized by correspondence to the shift of Intertropical Convergence Zone (ITCZ). Chl-a and SST correlate significantly and positively. It is believed that the optimal temperature for phytoplankton growth influences the temporal correlation distribution of Chl-a and SST. Rainfall patterns at the study site are monsoon-like, with a February peak and an August peak. There are indications of seasonal influence on Chl-a, despite the fact that this has no effect on trophic status. Anomalous rainfall and IOD phenomena affect the principal component (PC) of EOF mode- 1 anomaly Chl-a. It is hypothesized that development of Jakarta Bay reclamation in 2012 has led to alterations in fluctuation pattern of principal component of EOF mode-2 anomaly Chl-a. These alterations are attributed to changes in current patterns and speeds. One potential scenario involves the release of nutrients from the watersheds. These nutrients are then transported by rainfall and then enter the river, eventually reaching the Jakarta Bay. It suggested to increase dissolved nutrient in Jakarta Bay. The growth of phytoplankton is enhanced by environmental factors such as compatibility with SST and sufficient exposure to sunlight. This growth is marked by elevated concentrations of Chl-a. To enhance the management of water quality in the Jakarta Bay, it is imperative to implement enhancements in the monitoring system for Chl-a and the trophic status. Additionally, an early warning system should be established to proactively mitigate significant detrimental consequences. In Jakarta Bay, 11 sampling points were recommended for trophic status analysis based on a study of Chl-a variability from 2002 to 2022. The management of nutrient emissions from non-point sources can be accomplished with nature-based solutions that can be implemented from the regulatory side (by tightening oversight of point and nonpoint sources, implementing incentives and disincentives in the management of nutrient emissions from non-point sources, as well as good management of open green space), the domestic sector (by expanding the use of sewerage systems with environmentally friendly processing technologies and permaculture practices), the farming sector (by responsible and sustainable waste management), and the crop fishing sector (by sustainable fish feed and manure).