Aidil Sulfitra
Geografi Department, Faculty of Mathematics and Natural Science, Universitas Negeri Makassar, Jl. Mallengkeri Raya, Parang Tambung Urban Village, Tamalate District, Makassar, South Sulawesi, 90222

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pH, Dissolved Oxygen, and Salinity Dynamics in Indonesian Coastal Waters: A Systematic Literature Review Medar M Nur; Rosmini Maru; Hasmiani Hasmiani; Selvia Selvi; Aidil Sulfitra; Nasrul Nasrul
Jambura Geoscience Review Vol 8, No 2 (2026): Jambura Geoscience Review (JGEOSREV)
Publisher : Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/jgeosrev.v8i2.37362

Abstract

Tropical coastal environments across archipelagic regions face intensifying pressures from global climate anomalies and localized anthropogenic drivers, making systematic water quality monitoring critical for ecosystem sustainability. This systematic literature review (SLR) evaluates the spatiotemporal dynamics of pH, dissolved oxygen (DO), and salinity as fundamental physicochemical indicators of water quality within Indonesian coastal zones and connected oceanic frameworks. Utilizing the PRISMA 2020 framework guidelines, peer-reviewed international and regional articles published between 2018 and 2025 with active Digital Object Identifiers (DOIs) were systematically evaluated and synthesized. The synthesized findings indicate that declining coastal pH and DO concentrations are consistently driven by localized organic matter loading, microbial respiration, and progressive ocean acidification trajectories. Meanwhile, salinity fluctuations are predominantly governed by monsoonal precipitation shifts, equatorial winds, and freshwater riverine discharge. This review exposes a critical research gap regarding the historical scarcity of integrated, multi-parameter monitoring paradigms. Consequently, this study underscores the urgent necessity of transitioning toward centralized, real-time automated sensing networks and advanced predictive modeling frameworks, such as Artificial Neural Networks (ANN), to support evidence-based, adaptive coastal resource management policies across dynamic Indonesian coastal zones.