D01
Scenario development
PD Dr. Wolfgang Britz
University of Bonn | +49 228 73-2912 |
Summary
Project D01 will provide ex-ante land use cover and management scenarios reflecting different socio-economic developments. The scenarios with an annual resolution until 2050 will provide results at continental scale with sub-national detail. To consider interactions at regional and global scale due to market feedback, a recursive-dynamic global Computable General Equilibrium (CGE) model will be further developed and applied for the scenario quantification. This model covers all sectors of the economy with detail for sectors relevant for land use, and considers important drivers of structural change, such as income and demography dependent changes in consumption including diets. The storylines will be developed based on the Shared Socio-Economic Pathways (SSPs) from the Intergovernmental Panel on Climate Change (IPCC).
Graphical summary
Contribution to the CRC
The land use cover and management information provided by project D01 will be down scaled to grid level applying the methodology developed in project B04. The joint aim of both projects is to inform the coupled Earth-System-Model.
Approach
Project D01 will use and further develop CGEBox (https://www.ilr1.uni-bonn.de/en/research/research-groups/economic-modeling-of-agricultural-systems/cgebox), a modular platform for CGE modeling. In addition to updating the database, an expansion of the land use drivers covered in the model is planned. Within the framework of the five SSPs, scenario narratives with a focus on land use cover and management will be developed and quantified. The land use results will be subjected to a comprehensive sensitivity analysis and a socio-economic and ecological welfare analysis.
Main results in 2022
As foreseen in workplan under work package D01.01 for 2022, major drivers of land use change related to the five SSPs drivers were identified based on literature research. The following graphic shows the identified drivers, grouped into blocks, where the number of the arrows indicates their strength in the different SSPs. The selection reflects the available model mechanism and the possibility to arrive at quantified assumptions for each driver. The literature research and the selection of the drivers cannot be published as a separate paper and is therefore comprised in the publication on the land use results related to D.01.03. The work on the Data base development foreseen in 2023 started earlier Britz, W. (2022).
Note: LMH: Different assumptions for low, middle and high-income countries. Low-income countries use the assumptions of SSP3, middle- income countries of SSP2 and high-income countries of SSP1.
Main results in 2023
During 2023, the data base for the analysis was developed as foreseen in the work program under D01.02. The latest available GTAP data base Version 11 was made available (Chepeliev 2023). The 160 single regions or group of regions in the data base were outside of the European Cordex region aggregated following the grouping on the SSP related literature. For the European Cordex, the available country detail was maintained, leading to a data base with 47 countries respectively country groups. The GTAP data base covers around 14 products/sectors which relate to primary agriculture, fishing and forestry (crops, livestock) and 8 relating to food processing (meat, dairy, vegetable oil and cakes, other). The detail was increased to 40 for primary products and 21 food processing products (Britz 2022). The disaggregation uses a Linear Programming based approach documented in Britz 2021. The crop sectors were further broken down to an irrigated and non-irrigated variant, driving the number of sectors for primary agriculture, forestry and fishing to 92. In order to improve the land use detail for Europe, a data base for the so-called NUTS2[1] sub-national regions was developed, by combining various economic statistics into a consistent data set of estimated Value Added by sector and sub-region (available as https://svn1.agp.uni-bonn.de/svn/cgebox/gams/GTAPNuts2/gdp_NUTS2_V11.gdx). This includes the use of CORINE land use data to estimate land cover at the level at NUTS2. As the GTAP data base requires a paid-for license, the data can be shared with license holders, only. However, the underlying data for the splits are publicly available from FAOSTAT (https://svn1.agp.uni-bonn.de/svn/cgebox/data/FAO_2017_forSplits.gdx), the driver for the split utility of CGEBox to build the data base in two steps can be found at https://svn1.agp.uni-bonn.de/svn/cgebox/data/FAO_AT2050.gdx.
The second block in work package D01.02 relates to methodological improvements of CGEBox and G-RDEM. For instance, a more detailed nesting structure of the land use allocation was developed (https://svn1.agp.uni-bonn.de/svn/cgebox/gams/GtapAEZ/gtapAez_model.gms), the targeting of the crop land projections by the FAO improved (https://svn1.agp.uni-bonn.de/svn/cgebox/gams/GTAPRdem/fao_baseline.gms) and GDP content of products were rendered a function of GDP per capita. Various other improvements were integrated, such as improved algorithms to solve the model in large-scale recursive analysis. All code improvements are publicly available on the SVN repository. These improvements are used by the community of CGEBox users which includes, for instance, a group at the World Bank in Washington. There were used in work involving the PI (https://www.worldbank.org/en/country/romania/publication/country-climate-and-development-report-for-romania, https://openknowledge.worldbank.org/entities/publication/05c34aa3-67f6-44d1-bb41-46b191ef73c3, ) and show the successful transfer of project findings into policy relevant analysis. Findings building on the data base and methodological work were presented at the GTAP conference: Goebel and Britz 2023: A Computable General Equilibrium Modelling Approach to Assess Biodiversity Effects in Highly Detailed Global Long-Run Analysis, presented during the 26th Annual Conference on Global Economic Analysis (Bordeaux, France).
Main results in 2024
Following the workplan under work package D01.03, the identified in work package D01.01 were mapped into quantified assumptions (https://svn1.agp.uni-bonn.de/svn/cgebox/gams/scen/user_scenarios/ssp.gms[2]). Using the data base and improved model from D01.02, global scenario runs were conducted, see graphic below for an overview of the process. The scenarios include the latest macro-economic and demographic projections for the SSP1 released in 2024. The approach and results are presented in a paper which is close to submission. The land use projections are planned to be made afterwards available as a data in brief publication. The sensitivity analysis as foreseen in the work plan was conceptualized. Results were compared for run all drivers and each SSP as the default against a set-up where one of the drivers were not considered, resulting in about twenty sub-scenarios for each SSP.
Figure 1: Overview of modelling set-up
Note: G-RDEM and its features/ mechanism are highlighted in blue. Regions are run in blocks, and not all at once.
On-going work in 2025
Following the work plan, the work on down-scaling to grid level for the focus regions using the methodology and software developed in B03 has started by conceptualization the interfacing in close cooperation with B03. The improved recursive-dynamic module of CGEBox is presented in one-week interactive block course to PhD students from different European countries in March 2025.
Footnote
[1] NUTS: Nomenclature des Unités territoriales statistiques. For Germany, the 36 NUTS2 regions refer to the so-called “Regierungsbezirke” respectively “Laender” where these are both aNUTS1 and NUTS2 region.
[2] The SVN repository can be accessed in read-only mode with the userid cgebox and the password cgebox
References
Britz, W. (2022). Disaggregating agro-food sectors in the GTAP data base. Journal of Global Economic Analysis, 7(1), 44-75. https://doi.org/10.21642/JGEA.070102AF
Chepeliev, M. (2023). GTAP-power data base: Version 11. Journal of Global Economic Analysis, 8(2). https://doi.org/10.21642/JGEA.080203A
