Abstract:
The vulnerability of island nations to
catastrophic marine pollution and severe coastal
degradation - exemplified by the MV X-Press Pearl
disaster in Sri Lankan waters - reveals fundamental
structural limitations in traditional environmental
governance. Sri Lanka’s primary legislative frameworks,
the Coast Conservation and Coastal Resource Management
Act No. 57 of 1981 (as amended) and the Marine Pollution
Prevention Act No. 35 of 2008, depend primarily on post-
hoc reactive physical inspections and static, periodic
planning cycles. This study formulates a feasible legal
model that integrates Artificial Intelligence (AI),
Synthetic Aperture Radar (SAR) telemetry, multispectral
optical remote sensing, and automated data fusion into
Sri Lanka’s statutory framework. Through an analytical
examination of domestic legislation, international
conventions (UNCLOS, MARPOL 73/78, Basel
Convention), and recent environmental jurisprudence,
this paper identifies critical statutory lacunae regarding
data mandates, cross-border intelligence exchange, and
the evidentiary admissibility of autonomous algorithmic
detections. To resolve these deficiencies, this study
proposes two statutory draft amendments: (1) Section
12A of Act No. 57 of 1981, mandating an automated, real-
time "Smart Coastal Zone Management System" (Smart-
CZMP); and (2) Section 25A of Act No. 35 of 2008,
establishing statutory rebuttable presumptions of liability
derived from validated AI satellite surveillance alongside
procedural compliance with the Evidence (Special
Provisions) Act No. 14 of 1995. This legal framework
provides a proactive, technologically sovereign
mechanism to mitigate marine plastic accumulation,
coastal erosion, and maritime environmental crimes.
