Overview
This project offers an exciting opportunity to develop innovative methods using multi-sensor satellite data—including radar (Sentinel-1) and optical (Sentinel-2, and Landsat) imagery—to evaluate the effectiveness of water-based nature-based solutions (NBS) and quantify the economic value of the benefits they deliver.
About this opportunity
Water-based NBS, such as leaky dams, in-channel log jams, riparian buffers, and remeandering, are increasingly used to reduce flooding, improve water quality, enhance drought resilience, and support ecosystem recovery. In Cheshire and across the UK, many of these interventions have already been implemented, yet robust evidence of their real-world impact remains limited.
Working with Cheshire Wildlife Trust (CWT) and wider catchment partnerships, the student will build a geospatial database of existing and planned water-based NBS interventions. Using the satellite datasets, they will measure changes various hydrological (i.e., flood regulation, drought resilience, sediment retention, water quality) and ecological (i.e., vegetation growth, and habitat connectivity) outcomes before and after interventions. These environmental metrics will then be integrated into an economic model to estimate the value of water-based NBS to ecosystem services, specifically, avoided flood damage, water quality improvements, and biodiversity enhancements, producing evidence to guide future investment in water-based NBS across the UK.
This is a highly interdisciplinary project combining remote sensing, hydrology, ecology, and environmental planning and economics. The successful candidate will receive training in:
- Advanced GIS for mapping and analysing environmental datasets.
- Earth observation and remote sensing, including radar (Sentinel-1) and optical (Sentinel-2, Landsat) imagery, time-series analysis, and classification methods.
- Hydrological and ecological modelling to quantify flood attenuation, drought regulation, sediment retention, and habitat connectivity.
- Environmental valuation methods, including cost–benefit analysis and benefit transfer, to translate ecosystem service metrics into economic terms.
- Transferable skills, such as project management, coding (Python, R), stakeholder engagement, and science communication.
The research will take place within a supportive, collaborative environment. The student will be embedded across multiple research groups, including the Geographical Data Science Lab, Planning, and Environmental Assessment and Management, and Environmental Change, benefiting from access to their combined expertise, high-performance computing, specialist software, and training courses. Strong links with CWT and partnering organisations will provide real-world context, site visits, and opportunities for validation and engagement with stakeholders, giving the student a unique, interdisciplinary perspective and direct exposure to applied conservation challenges.
By the end of the PhD, the student will have developed a scalable, satellite-based framework for monitoring the hydrological, ecological, and economic impacts of water-based NBS. The project will generate urgently needed evidence for policymakers and practitioners, supporting investable, evidence-based approaches to water catchment management in the UK and internationally.