Community Research and Development Information Service - CORDIS

Periodic Report Summary 1 - GEOSINPO (Geo-Spatial Modelling Informing Policy)

Policy makers are facing challenges of managing complex urban and environmental systems influenced by global factors. These factors include as population growth, migration, recession, climate change as well as actions by local actors such as parties or companies who direct the development according to their own vested interest which may not conform with a broader public interest.

Confronted with such complexity, decision makers need adequate tools to better understand and evaluate the effects of policy interventions in urban regions. Such pressures led to the development of numerous models covering different discipline-specific areas. Nevertheless, the interconnected character of human and natural systems such as demographics, transportation, infrastructure, economics, land cover, climate, air and water requires an integrated approach in both decision making and modeling.

However, it is an expensive and time-consuming task to develop a new model. Moreover, a single model cannot provide answers required for complex decision making based on multiple criteria. Coupling models are often applied to make use of existing models and analyse complex policy questions. The model coupling approach developed in the GeoSInPo project aims to make integration of existing models easier, overcoming challenges such as differences in programming languages, unavailability of the source codes or licensing restrictions.
A loose model coupling approach was developed during the outgoing research period to build an integrated Spatial Decision Support System (SDSS). With the use of Python wrappers, the implementation of the couplers is separated from the models’ source codes. This gives a flexibility, which can help in terms of portability, performance and maintenance of the model codes. The approach was successfully applied for the Baltimore-Washington Region coupling five independently developed models: Simple Integrated Land Use Orchestrator (SILO), Maryland Statewide Transport Model (MSTM), Building Emission Model (BEM), Mobile Emission Model (MEM), Chesapeake Bay Land Change Model (CBLCM). The integrated suite is now being applied to simulate and explore alternative scenarios of the region for 2040.

The SDSS outputs include several useful socio-economic indicators, covering: population and employment, transport flow, land use, building and mobile emissions, and more. It is known that the changes in transportation, land use and human behaviour in general impact also on nutrient loading and water quality in a region. Translating the effect of socio-economic alterations into nutrient loading in Chesapeake Bay for example will help us to explore the changes in flow and nutrients loads into the Bay and design more effective public policies and restoration plans. Adding environmental models to the policy decision making process will help to assess how social-economic changes and policy decisions in the Washington-Baltimore Region ultimately impact water quality in the Chesapeake Bay improving policy decision making. Aiming to support improved policy analysis and decision making, the following environmental models were also explored for further enhancement of the integrated suite: Integrated Transport and Health Impact Modelling Tool (ITHIM), Hydrological Simulation Program - Fortran (HSPF) and Chesapeake Bay ROMS Community Model (ChesROMS). The attached figure illustrates already coupled models and the models currently being considered to be added to the suite.

More details are provided in the recently published papers by Shahumyan et al. (2016) and by Shahumyan and Moeckel (2015, 2016). More information on the project is available in the project website at

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