Models

GLOBIOM

The Global Biosphere Management Model (GLOBIOM) has been developed and used by the International Institute for Applied Systems Analysis (IIASA) since the late 2000s. The partial-equilibrium model represents main land use sectors, including agriculture and forestry. The supply side of the model is built-up from the bottom (spatially explicit land cover, land use, management systems and economic cost information) to the top (regional commodity markets). This detailed structure allows a rich set of environmental and socio-economic parameters to be taken into account.

G4Mm and G4M

The Global Forest Model (G4M) is a geographically explicit agent-based model to assess land use change decision making. G4M is designed to provide projections of afforestation and deforestation rates, forest management options and respective carbon dioxide emissions and sinks, and their response to climate policies in a form of carbon tax or incentive payments.

DownScale

The Downscaling module implements a series of workflows to create high resolution outputs from GLOBIOM model runs. This module is based on a cross-entropy optimization model with a flexible setting of priors, including biophysical and econometric components.

CWatM

The CWatM model represents one of the new key elements of IIASA’s Water program to assess water supply, water demand and environmental needs at global and regional level. The hydrologic model is open source and flexible to link in different aspects of the water energy food nexus. CWATM will be a basis to develop a next-generation global hydro-economic modeling and will be coupled to the existing IIASA models like MESSAGE and GLOBIOM.

MARINA

ECHO

ECHO is a bottom-up system analysis framework which can be used to develop integrated, long-term planning strategies for the water system. It can be used to inform the design of cost-effective and sustainable water policy decisions and to address the impacts of future changing socio-economic and climatic conditions on water system. The Global Hydro-economic Model is a new element of IIASA’s water program which provides a technology rich basis for estimating water system dynamics over a long-term, multiple period time horizon. The model operates at global, regional and basin scales.

ibis.iSDM

The ibis.iSDM model is an open-source and easy to use R-package for creating single and integrated, e.g. those using multiple data sources, species distribution models with primary biodiversity observations and is developed by IIASA’s BEC program. Ibis.iSDM supports a range of machine-learning and Bayesian modelling approaches, primarily fitting Poisson-point-process models (PPMs) and flexibly allowing to incorporate biodiversity habitat and threat information through priors and offsets. The ibis.iSDM model will be coupled to the spatial-explicit outputs of the GLOBIOM-DownScale and other models such as CWatM or EPIC in a DPSIR framework.

EPIC

EPIC-IIASA quantifies agricultural production as well as environmental externalities for a range of crop management systems at global scale. The model is used to assess the main global agricultural systems in response to management interventions such as cropping practices or fertilization and irrigation options, and changing environment, including climate change and soil degradation. Besides which EPIC is used to compare cropland management systems and their effects on environmental indicators like water availability, nitrogen and phosphorous levels in soil, and greenhouse gas emissions.

FLAM

The wildFire cLimate impacts and Adaptation Model (FLAM) is able to capture impacts of climate, population, and fuel availability on burned areas. FLAM uses a process-based fire parameterization algorithm that was originally developed to link a fire model with dynamic global vegetation models. The key features implemented in FLAM include fuel moisture computation based on the Fine Fuel Moisture Code (FFMC) of the Canadian Forest Fire Weather Index (FWI), and a procedure to calibrate spatial fire suppression efficiency.

BeWhere

BeWhere is a techno-economic engineering model for renewable energy systems optimization. It identifies the localization, size and technology of the renewable energy system that should be applied in in a specific region. The economy of the supply chain is calculated with respect to the economy of scale of the corresponding renewable energy system.