AIM: Soils are a key component of terrestrial ecosystems and provide multiple ecosystem services to humans, including the provision of food from agriculture. Soil organic carbon (SOC) loss due to intensive agricultural practices, and climate change is a major threat to global food security. Current field-based approaches provide a limited understanding of the nature, scale and spatial variability of soil carbon loss. Hence our ability to accurately assess the impacts of climate change and farming practices in a way that will mitigate against SOC loss, is severely limited. This project will produce accurate measurements at the necessary spatial and temporal resolution to provide new insights in the soil carbon dynamics at site, landscape and regional scales. We aim to develop an integrated state-of-the art remote sensing tool that may be applied to monitor spatial and temporal patterns in soil health, facilitating novel agricultural practices, improving SOC sequestration and delivering climate change mitigation and adaptation targets.
OBJECTIVES: O1 Design, develop, and deploy innovative sensors mounted on Unmanned Aerial Vehicles (UAVs) across test sites to measure topsoil carbon, soil moisture, and spatial patterns of soil loss, in response to i) short-term weather events and (ii) land management practices; O2 Use satellite-derived data to upscale from site to landscape to regional-scale processes by modelling changes to carbon and water storage; O3 Use our findings to drive future soil management policy and practice.
This PhD project will be led by the University of Hull and involve a number of partner research organisations in Europe including the University of Lyon, and will focus upon two types of farming system; 1) arable land in the UK (e.g. potato farms, Herefordshire; cereal farms, East Yorkshire), and 2) vineyard agroecosystems, Beaujolais and Burgundy, France.
Arable, cereal farming and vineyards can have a high risk of soil erosion and degradation, resulting in the loss of SOC. Increasing SOC stocks to cropping systems has the potential to contribute to climate change mitigation through SOC sequestration and to enhance soil quality. The concept of soil carbon sequestration is a key measure in both climate mitigation and adaptation. The potential of “carbon farming” to sequester CO2 emissions while regenerating degraded agricultural soil has been viewed positively by the EU parliament in the attempt to scale up the EU’s ambition for obtaining climate neutrality by 2050. Agricultural soils in the EU contain around 14 billion tonnes of carbon in the topsoil, compared to the 4.4 billion tonnes of greenhouse gases emitted annually by all the EU’s 27 countries. ‘Carbon farming’ is included among the main Good Agricultural and Environmental Conditions (GAECs) of the eco-scheme, the new green architecture in the EU’s post-2020 Common Agricultural Policy (CAP). GAEC-2 aims to protect carbon-rich soils, considered among the most effective carbon sinks and will be applied to all eligible agricultural land. The EU has recognised that pilot initiatives are needed at local or regional level in order to gather experience to upscale carbon farming.
The proposed research will focus on enhancing SOC in depleted arable and viticultural land, with the vision of improving productivity and resilience. We will integrate state-of-the-art sensor technologies to make new discoveries on carbon sequestration in agricultural soils; assessing climate-change and farm management impacts. Data shall be captured through UAV-mounted sensors and satellite images. UAV-mounted sensors have the flexibility to acquire remote sensing data at ultra-high spatial, spectral and temporal resolution overcoming the critical limitations of satellite and airborne-mounted sensors. Recent developments in UAV platforms and sensors offer researchers for the first time the capability of acquiring spatial datasets with sufficient spatial, spectral and temporal coverage to provide new insights into key climate and landscape processes. We will measure spatio-temporal changes in SOC using hyperspectral sensors and Fourier Transform Infrared spectrometry, and quantify SOC budgets through coupling these data with UAV-LiDAR. We will also employ satellite-derived datasets with different spatial and temporal resolutions (e.g. Goes-16, Meteosat, Modis-Terra, Landsat, Sentinel-2, Prisma, Planet, Cbers), that now provide high-quality data at low cost. This project will be highly innovative in the type and integration of UAV-sensors deployed, the range and accuracy of soil composition parameters being determined, and the ability to upscale from plots to catchment to regional scales using new emerging satellite datasets.