Successful coastal management requires extensive water quality monitoring for nutrients released from terrestrial agriculture and human sewage. Reducing these inputs is essential for achieving clean and healthy seas now, but most importantly, habitats that are targets for restoration (seagrass, oysters and saltmarsh) require good water quality to be healthy and thrive. If poor water quality (a key driver for the loss and degradation of these habitats) has not improved then the success of seascape restoration will be in doubt. For over 20 years relevant data (e.g. nutrients, turbidity) have been collected by agencies (e.g. Environment Agency) from hundreds of sites. These are then placed in publicly-accessible repositories. However, these data-sources are extremely challenging to work with due to a) database size (several million data points), b) frequent changes in sampling techniques; c) inconsistent data coding and d) limited site-specific data (Richir et al., 2021). Thus, this wealth of big data (BD) information is inaccessible and unusable in the current format. Therefore, decisions on the location of restoration without access to water quality data is a significant risk for the success of restoration projects.
BD analysis is now at the forefront of coastal monitoring and has significant potential for addressing key marine challenges. This project will develop, test and validate BD approaches to maximise the chances of success for restoration in the Solent coastal system.
There are three objectives that the project will address:
The success of the project will be measured against the objectives. However, the significance and legacy will be providing data that informs seascape restoration to maximise the success of all planned restoration projects within the Solent.
Project lead: Prof Gordon Watson, Institute of Marine Sciences, University of Portsmouth.