Coastal Vigilance: Harnessing AI, Remote Sensing, and Citizen Science for Enhanced Observation and Monitoring of Land-to-Coastal Pollutant Transport

Upstream pressures on coastal ecosystems need to be understood and managed within the context of a changing climate and land use. These impacts on water quality are moderated by catchment-specific hydrology, so there is no single modelling solution to suit every catchment at appropriate spatio-temporal scales. We need innovative approaches to measure the impact of observable catchment properties and non-observable drivers of water quality.

The proposed project deploys Machine Learning (ML) trained on remote sensing and in situ observations, to work with statutory monitoring, water utilities and citizen science to dynamically improve observation and monitoring of pollutant transport from land to coastal zones.

This project aims to quantify potential downstream impacts of pollution on intertidal and marine organisms, habitats, and biodiversity. The work will enable early detection and tracing of pollution events alongside targeted, microscale observation of diffuse pollution sources, to facilitate timely response measures and reduce ecological and economic damage to coastal ecosystems.

A data-driven approach empowers stakeholders with accurate models, pollutant maps, and monitoring systems to make informed decisions for catchment-to-coast resource management. A ML interface reduces the need for explicit hydrological models and may benefit transferability (training data need and cost) of the solution to other catchments and regions.

The proposed approach supports wider development of conservation plans, management strategies, and policies to safeguard marine resources. Engaging citizen scientists raises awareness and stewardship and facilitates a culture of sustainability in coastal communities. The focus on observing and monitoring pollutant transport dynamics provides vital information for sustainable coastal development and use of resources.

By identifying potential risks and vulnerabilities in coastal areas, the project enables informed land-use planning, infrastructure development, and conservation measures.

These actions minimize the often-negative impacts of human activities on marine resources, ensuring the long-term sustainability of coastal ecosystems and the communities dependent on them.