Application of remote sensing derived plume exposure and water quality guidelines in data limited coastal waters: A case study of Marine Protected Areas and habitats in Sri Lanka
Authors:
- Lenka FronkovaLFLenka Fronkova
- Naomi GreenwoodNaomi Greenwood
- Rekha H.M.R.S. RajasingheRRRekha H.M.R.S. Rajasinghe
- Manjula S.O.M. AmararathnaMAManjula S.O.M. Amararathna
- Susantha UdagedaraSusantha Udagedara
- Michelle J. DevlinMDMichelle J. Devlin
- Charlotte ReeveCRCharlotte Reeve
- William A. ProcterWPWilliam A. Procter
- Tiago SilvaTSTiago Silva
- Michael DayMDMichael Day
- David B. SivyerDSDavid B. Sivyer
Preprint
- 21 April 2026
- preprint
- Published by Elsevier in SSRN Electronic Journal
Abstract
Marine Protected Areas (MPAs) in Sri Lanka contain diverse coastal and marine habitats that provide invaluable ecosystem services. These habitats face water quality degradation from adverse human activities, such as limited treatment of industrial, fishing and domestic waste, marine traffic, illegal landfills or cross-boundary litter pollution. Historically, water quality surveys in Sri Lanka have been opportunistic and short-lived. In absence of regular in-situ water quality data, this study uses remote sensing Sentinel-3 OLCI between 2017-2023 to map the exposure from riverine plumes to MPAs and their habitats in Sri Lanka’s coastal waters. It also applies water quality guidelines from Australian coral and mixed inshore ecosystems and compares them to locally derived Sri Lankan chlorophyll and total suspended matter from Sentinel-3 OLCI level 2 in most plume exposed MPAs. The results show the first spatial zones that can be used for regular water quality assessments in Sri Lanka and coastal areas the most impacted by potential land-based pollution. Additionally, local water quality matrices for Sri Lankan waters were derived, since the regional thresholds applied from the Australian ecosystems are three times smaller and do not reflect processes along the Sri Lankan coast. Broader implications of this case study are a cost-effective method for remote ecosystem management that can identify the areas suffering from poor water quality and monitor their status, hence contribute to the ecosystem conservation. However, any baseline remote sensing derived water quality guidelines still need to be calibrated by local in situ data on water quality and habitat condition.Keywords
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