Figure 1 provides a basic overview on ESM’s Integrated Modeling Cluster and its principal functioning. The Integrated Modeling Cluster consists of 3 bottom-up core models including 2 biophysical process based models - for forestry (G4M (see #1), Global Forest Model, www.iiasa.ac.at/g4m) and for agriculture (EPIC (see #2), Environmental Policy Integrated Climate Model, www.iiasa.ac.at/epic). Both of these biophysical models are geographically explicit and have been designed as “stand-alone” models for optimal calibration and output interpretation as well as in order to generate computational advantages) and can at the same time be linked and integrated in the cluster to provide essential input data to the global economic land use model (GLOBIOM (see #3), Global Biosphere Management Model, www.iiasa.ac.at/globiom).
Optionally, also an engineering model with a techno-economic approach for cost-optimal scaling and siting of renewable energy systems (BeWhere (see #4), www.iiasa.ac.at/bewhere) can be integrated to the cluster, i.e. G4M provides input data on harvestable biomass availability. Presently, a continuous linkage between BeWhere and GLOBIOM is under development.
In addition, there is a tool called Geo-Wiki, which is primarily concerned with improving global land cover. This tool is used to validate land cover maps, collect training and validation data for the development of new land cover products and acts a visualization platform for different spatially explicit data sets. Geo-Wiki feeds information into the Integrated Modeling Cluster since global land cover is a crucial input to the GLOBIOM model while more accurate forest cover is a necessary component to G4M. Future developments include visualization of model outputs from the Integrated Modeling Cluster using Geo-Wiki.
Figure 1: ESM’s Integrated Modeling Cluster featuring the main (type of) models and their inter-linkages.
The models GLOBIOM, EPIC, and G4M have been used since several years in an integrated modeling framework at IIASA-ESM. The partial equilibrium model GLOBIOM (details see next section of this report) simulates land use based activities globally with a grid-cell based bottom-up representation.... Biophysical parameters on the crop and forest sectorare supplied by the more specialized models G4M for forestry and EPIC for agriculture (also here see next section for more detailed model descriptions). Global demand and trade for agricultural and forestry products are represented for 30 economic regions (or 53 for the version with disaggregated EU). MMarket equilibrium determines allocation of land use and processing activities to maximize the sum of producer and consumer surplus subject to resource, technological, and policy constraints. The general concept and structure of GLOBIOM is similar to the US Agricultural Sector and Mitigation of Greenhouse Gas (ASMGHG) model.
EPIC supplies to GLOBIOM detailed information on management-related yields according to fertilizer and irrigation rates. EPIC is set up globally for 20 crops (barley, dry beans, cassava, chickpea, corn, cotton, cowpea, ground nuts, millet, oats, potatoes, rapeseed, rice, rye, soybeans, sorghum, sugarcane, sunﬂowers, sweet potatoes, and wheat). Four management systems are simulated by EPIC and implemented in GLOBIOM (irrigated, high input – rainfed, low input – rainfed and subsistence management systems). For each management system, EPIC provides GLOBIOM with information about crop yield, fertilizer and water requirements, as well as various environmental parameters including carbon and nutrient balance, and the connected greenhouse gas emissions, nitrogen leaching, soil erosion, and other biophysical indicators.
On the forestry sector side, G4M supplies GLOBIOM with information on mean annual increment, maximum share of biomass usable as saw logs in the mean annual increment, and harvesting costs. G4M also supplies GLOBIOM with consistent accounts of carbon stocks in forests which are then used to assess GHG emissions related to deforestation. In an iterative procedure, G4M in turn uses GLOBIOM projections on wood and agricultural land prices, and wood demand quantities to consistently estimate future forest dynamics at high spatial resolution (currently at a 0.5° x 0.5° resolution).
Additionally, GLOBIOM can be linked to macro-economic or energy models to capture drivers and feedback associated to different future scenarios on population, GDP, carbon prices, bioenergy demand, etc… For instance, linkages have been developed with the JRC global energy model POLES (Prospective Outlook for the Long-term Energy System) for regions outside Europe or the PRIMES model for EU28 countries. GLOBIOM is also linked to the IIASA energy model used for climate change mitigation assessment, MESSAGE.
The model development has been started with the establishing of G4M in 2006/7 by the global land use management group under IIASA’s Forestry Program (FOR), led by Dr. Michael Obersteiner. EPIC has been brought from the US to Europe and jointly developed into a European agriculture model in collaboration between BOKU University, Vienna, and IIASA’s FOR Program during 2004-2010. The development of GLOBIOM has been started in 2006/7 at FOR Program’s global land use management group and also BeWhere has been developed by the same group starting in 2007.
The ESM Integrated Modeling Cluster in its present form has been formally established in 2011 by the new leadership of IIASA’s Ecosystems Services and Management (ESM) Program (following the merging of IIASA’s former FOR and LUC Programs into the new ESM Program). The strategic background has been to put emphasis on the further development of the Integrated Modeling Cluster and base it on methodologically new and innovative models in order to adequately address the key topics of IIASA’s new Food and Water Challenge Area. The 4 models described earlier have been selected to form the cluster’s core and have subsequently been further developed and completed with new and innovative components. G4M has been further developed for REDD policy assessments;;EPIC model runs have been expanded from a European to a global scalescale, GLOBIOM has been developed to provide a unique global economic land use model that includes besides agriculture also the forest sector, as well as an innovative livestock component (in collaboration with ILRI); and BeWhere was turned from a local bioenergy model into a global renewable energy systems optimization model.
An impressive demonstration of the cluster’s capacity and functionality has been inter alia WWF’s Living Forest Report (c.f. Taylor, 2011; Kraxner et al., 2013) in 2011, which has been entirely based on the cluster’s models (i.e. EPIC, G4M and GLOBIOM), addressing in several chapters global forest-related topics such as avoiding deforestation, forest management, biodiversity protection, GHG emissions, land use change, bioenergy, fertilization, water demand, food security, agricultural intensification, global diet patterns etc. This large-scale effort together with WWF has been IIASA’s contribution to the International Year of Forests in 2011 and achieved high visibility also within policy makers.
In addition to putting emphasis on integrating and improving the sector-specific components of forestry and agriculture within the GLOBIOM model, new collaborations have been started in order to develop further complementary components of GLOBIOM. Based on the excellent collaboration with respect to the livestock sector inclusion together with ILRI and CSIRO, an extension towards the aquatic food system (in order to complete the land-based food sector with the water based production system) is planned. Furthermore, the (food sector-related) mining sector developed into a large-scale driver for land use change, i.e. for deforestation etc. - often coming along with socio-economic aspects such as tenure and ownership rights. These important sectors and issues have to be included in future land-use change assessments and hence will also have priority with respect to collaboration-based development of GlOBIOM. Generally, there is a trend towards globally consistent national (regional/local) approaches (as have been started e.g. in Europe, Brazil, the Congo Basin and Indonesia) which will find its continuation in NMO countries of areas such as South Asia, and in general in most parts of the developing world together with CCAFS.
Further improvement of integration of the ESM models, including hard-linking, is foreseen. For instance, many unique features of G4M will be directly transferred to GLOBIOM.
Climate change impacts are in the medium term likely to affect the agricultural sector more through changes in the frequency of extreme whether events than through changes in the average levels of the yields. Therefore innovative approaches going byond the simple equilibrium are required. We will further pursue the already initiated work on a stochastic version of GLOBIOM to better capture these phenomena.
With respect to G4M it is planned to improve the representation of tropical forest systems and species in the model in order to improve accuracy and reduce uncertainties within its application in the REDD+ field. Furthermore, first global runs are presently carried out that take climate change explicitly into account. We also plan to improve estimation of forest management emissions by distinguishing between various wood assortments and their use for industrial purposes.
In the field of biophysical agriculture modeling, IIASA’s EPIC team at ESM will put further efforts into global crop modeling and extend the first results towards the 20 most important crop types. Additional improvements are expected from the developments of G-EPIC at IIASA but also through collaboration e.g. with Beijing Forestry University in China.
For BeWhere it is planned to improve its linkage to GLOBIOM by putting emphasis on further developing its global component. Here especially renewable energy systems such as photovoltaic – based energy production, but also wind- and hydro power, or waste to energy and fertilizer will be investigated. First national approaches and studies with respect to BECCS systems have been developed and further improvement of logistics, technologies and scenarios is being worked on. Additionally, there are plans to also link up to the livestock sector with respect to e.g. optimization of locations for slaughterhouses.
It is an overall aim for ESM models to put continuous effort into the consideration and inclusion of relevant (global) socio-economic parameters into our approaches.
Last edited: 03 September 2014
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