Project Description
Hosted at British Geological Survey
Supervisors
Dr Michael Watts, British Geological Survey- contact me
Professor William Blake, University of Plymouth, School of Geography, Earth and Environmental Sciences (Faculty of Science and Engineering)
Dr Olivier Humphrey, Inorganic Geochemistry, British Geological Survey
Dr Ruth Njoroge, University of Eldoret, School of Environmental Sciences
Background
The Winam Gulf catchment of Lake Victoria has historically been affected by poor land management practices leading to soil erosion, loss of agricultural productivity, flooding and downstream impact on lake ecology and associated fisheries. A gap in local knowledge/data and technical capacity to coordinate and deliver usable data tools was identified. This gap inhibits the dynamic understanding of the impact of soil degradation on soil-to-crop dynamics and subsequent impact on lake ecosystem/human health via the food chain. This is particularly pertinent given the growing importance of aquaculture to economic and food security in the Lake Victoria basin. Limited resources to monitor and regulate land degradation and inputs into the lake environment require scalable geospatial tools to direct limited resources for the mitigation of land degradation.
Methodology
The project will encompass two principle tasks:
(1) Landscape-farm scale survey to examine how different land management scenarios impact soil erosion and subsequent effect on land-to-lake dynamics using isotope tracer and source apportionment methodology at test sites in the Winam Gulf.
(2) Explore use of remote sensing data and machine learning-ML to identify potential for upscaling a GIS model versus field collected geochemistry data to inform areas that would benefit from soil erosion mitigation and protection from land clearance.
Training
To achieve these tasks, the student will receive training in field collections and community engagement, specialist laboratory techniques and data/statistical techniques in two phases:
(1) Using on-going data capture, evaluate the potential apportionment of soil/sediment chemistry to sources and locations from established field experimental plots and catchments-valleys identified from baseline data using isotope tracer and source apportionment.
(2) Incorporation of remote sensing data with field collected data to provide a predictive model for soil erosion at local and regional scales.
Person specification
The candidate should have an earth/environmental science or chemistry degree and willing to undertake fieldwork in Kenya. An aptitude for laboratory work and data handling skills would be desirable.
Acceptable first degree subjects: Chemistry, Geology, Environmental Sciences