The project aims to improve our ability to model the impacts of climate change on agricultural yields in Peru. Soil characteristics directly link to quality and quantity of crops produced. Within this project you will undertake laboratory analysis of Peruvian soils to provide improved soil inputs for robust yield modelling
Department: Meteorology
Supervised by: Prof. Joy Singarayer
Despite steady economic growth nationally over the last 15 years, a high percentage of the rural population in the Peruvian Andes continue to live in chronic poverty. The agricultural system in these rural areas has pre-Hispanic foundations of landscape transformation through sophisticated, highly organised engineering. However, lack of investment makes rural communities highly vulnerable to climate change. Climate change has already seriously affected the productivity of important staple crops, such as potato and maize, causing substantial annual agricultural losses. Growing insecurities are exacerbated by lower economic opportunities in rural areas. It is vital for adaptation decision-making that we understand how crop yields will be affected by future climate change. We are working on a wider project (called CROPP; Climate Resilience and Food Production in Peru) with Peruvian partners and stakeholders in these communities to address these challenges, involving modelling of climate change and crop yields. One major source of uncertainty in modelling crop productivity is in the characterisation of soils parameters, for which there is little data from our study regions in Peru. The project will undertake hands-on laboratory analysis to quantify soil characteristics (e.g., texture, bulk density, organic carbon). The results will be used to assess the sensitivity of the model to the soil parameter inputs. The project will also review the literature on crop yields in Peru in order to better evaluate the crop yield model.
The student will undertake three sections of work: [Week 1] Perform a literature review of observed crop yields in the Andes. Collate information into a brief written summary with tables of quantified information where provided, which will enable us to constrain the crop model we are using in the wider project. This can be done remotely if this suits the student. [Weeks 2-4] Undertake laboratory experiments to characterise agricultural soil samples that we have previously collected from various locations in the Peruvian Andes. The laboratory tests will be carried out in SAGES under the direction of Nick Branch and Andrew Wade, and include: • Soil texture analysis • Bulk density and porosity • Total organic carbon and nitrogen • pH and conductivity • Cation exchange capacity [Weeks 5-6] Use the laboratory results and literature review as inputs to the crop model set-up to simulate our field locations in Peru, and run some simple tests to gauge sensitivity of the model results to the soil characteristics input. This will be done with support from Joy Singarayer and can be done remotely if needed.
It would be beneficial for the student to have a background in an environmental science subject (e.g., geographical science, meteorology, agriculture). Familiarity with undertaking laboratory work in general would be helpful, although we don’t expect the student to have done the specific analysis intended here.
The student will develop independent research skills of analysing and synthesising scientific literature. They will develop capabilities in professional laboratory procedures and analysis. The student will develop an understanding of computer modelling, including model parameterisations, evaluation, and uncertainties. Through attendance at wider project meetings and with supervisors the student will develop experience of communicating with other stakeholders (e.g., NGOs).
Place of work for literature review and modelling is flexible and can be done remotely or within the Meteorology department. The laboratory analysis will be done in person in Geographical Sciences.
7 hours per day, with flexibility by agreement
Wednesday 05 July 2023 - Wednesday 30 August 2023
The deadline to apply for this opportunity is Monday 3rd April 2023. Students should submit their CV and Cover Letter directly to the Project Supervisor (click on supervisor name at the top of the page for email). Successful candidates will be invited for an interview.