Developing high-resolution above- and below-ground 3-D carbon maps for farm and land-D carbon maps
Lead Research Organisation:
CRANFIELD UNIVERSITY
Department Name: School of Water, Energy and Environment
Abstract
Stelina has successfully secured a place on the CENTA2 Doctoral Training Programme starting in September/October 2019. The aim of the PhD is to develop and evaluate procedures for developing high resolution 3D map/models of below- and above ground carbon that can be applied at farm- and landscape scale. It is anticipated that the model will be useful in high-resolution assessments of natural capital, assessments of the effect of different farm practices on carbon storage, and could help inform future agri-environment regulations.
The UK is seeking to minimise climate change by reducing net greenhouse gas (GHG) emissions by storing higher levels of carbon on agricultural and forest land. GHG emissions are the greatest negative environmental effect of rural land use in the UK, carbon storage is a form of natural capital, and maps of soil and above-ground carbon storage have been produced for England at 1 km resolution (CEH 2018). Whilst national maps exist, most land management decisions are taken at a farm- or landscape-level, and a 1 km resolution is insufficient to examine the effect ofmanagement options such as tree planting, hedgerow expansion, and conservation tillage (Upson et al. 2016; Axe et al., 2017; Giannitsopoulos et al. 2019). Hence the aim of this PhD is to develop and evaluate procedures for developing high resolution 3D map/models of below- and above ground carbon that uses innovations in digital technology and recent research results, and which can be applied at farm- and landscape scale (Fig 1). The anticipated model will build on a vertical resolution for soil C model of 10 cm (as used by Veronesi et al. 2014), but increase the horizontal resolution to allow the examination of the effect of changes in field management and landscape features such as hedgerows. Such a map/model will be useful in high-resolution assessments of natural capital, assessments of the effect of different farm practices on carbon storage, and could help inform future agri-environment regulations.
The UK is seeking to minimise climate change by reducing net greenhouse gas (GHG) emissions by storing higher levels of carbon on agricultural and forest land. GHG emissions are the greatest negative environmental effect of rural land use in the UK, carbon storage is a form of natural capital, and maps of soil and above-ground carbon storage have been produced for England at 1 km resolution (CEH 2018). Whilst national maps exist, most land management decisions are taken at a farm- or landscape-level, and a 1 km resolution is insufficient to examine the effect ofmanagement options such as tree planting, hedgerow expansion, and conservation tillage (Upson et al. 2016; Axe et al., 2017; Giannitsopoulos et al. 2019). Hence the aim of this PhD is to develop and evaluate procedures for developing high resolution 3D map/models of below- and above ground carbon that uses innovations in digital technology and recent research results, and which can be applied at farm- and landscape scale (Fig 1). The anticipated model will build on a vertical resolution for soil C model of 10 cm (as used by Veronesi et al. 2014), but increase the horizontal resolution to allow the examination of the effect of changes in field management and landscape features such as hedgerows. Such a map/model will be useful in high-resolution assessments of natural capital, assessments of the effect of different farm practices on carbon storage, and could help inform future agri-environment regulations.
Organisations
Studentship Projects
| Project Reference | Relationship | Related To | Start | End | Student Name |
|---|---|---|---|---|---|
| NE/S007350/1 | 01/10/2019 | 30/09/2027 | |||
| 2276184 | Studentship | NE/S007350/1 | 01/10/2019 | 31/03/2023 | Stelina Beka |
| Description | The PhD reviewed, developed, applied, and evaluated scalable and robust methods for creating fine-scale maps and models for above and below-ground C stocks for potential use by farm and landscape managers |
| Exploitation Route | Developed tool can be used to estimate farm based baseline carbon stocks |
| Sectors | Agriculture, Food and Drink,Environment |