Keywords: Sustainable development, integrated modeling, transport, land-use, energy, environment, data assimilation, calibration, sensitivity analysis, modularity.
Activities: The aim of STEEP is twofold: – to identify and assess the relevant factors for a transition to sustainability at local (sub-national) scales. – to develop mathematical and computational decision-making tools to help decision makers in the implementation of this transition.
To this effect, we take advantage of various existing energy / environment / land-use / transport models. These models are designed to simulate the effects of a given policy, or to optimize a policy choice under constraints. Possible constraints can be for example to reduce pollutant emission, satisfy heating demand, limit or avoid impacts of land use on ecosystemic services, increasing sustainable transportation offer while reducing global mobility demand etc. The mutual dependence of the phenomena that must be considered in such models makes them complex to build, and difficult to handle and improve. Some flexibility can be introduced by considering independent modular elements whose outputs are designed to comply to generic requirements ; this allows the model-builder to combine them in a simpler way to update the state of the system. Each module deals with a single issue, e.g. the transport system, the economic system, the socio-economic demographic distribution etc. LEAM (Land-use Evolution and impact Assessment Model) is a state-of-the-art example of such a modular model, specialized into the analysis of land-use evolution. The merging of all module outputs to get a consistent result is a critical element of the model. Also, in practice, this merging has to be carefully calibrated on real data to get relevant results for decision-makers. In LEAM, a genetic algorithm is applied to estimate the relative weights of the various land-use drivers.
In this context, the purpose of this PhD project is twofold:
- First, the LEAM framework will be used to build a modular model adapted to the Grenoble, Lyon and Chambery employment areas. These zones are a mix of urban, peri-urban, agricultural and natural or semi-natural (sometimes protected) areas. The analysis of transition to sustainability in these areas involves two specific features that will be explicitly taken into account in this work: (i) the peculiar topography (valleys and mountain ranges) and (ii) the evolution from a wet to a drier, more mediterranean-like climate over the course of the next decades.
- In parallel, a specific attention will be paid to the merging process and the calibration, in terms of methods, choices of the weighting function, and of determination of its parameters. Various techniques will be explored, such as Bayesian model selection, data assimilation approaches, learning methods, and multi criteria decision analysis. The sensitivity of the results to these choices will also be evaluated.
Environment: The project will be carried out in the STEEP lab at INRIA Rhône-Alpes, under the supervision of Dr. Emmanuel Prados (INRIA). This position is offered at the Rhône-Alpes Research Unit of INRIA, located near Grenoble and Lyon. The Unit includes more than 700 people, within 34 research teams and 10 support services.
Profile and conditions for applicants: This PhD position is aimed at a large range of young researchers with knowledgeknowledge in various scientific domains such as applied mathematics, computer science, economic modeling, energy systems, etc. Knowledge in programming languages is strongly desirable. Knowledge in applied mathematics is appreciated. Also, experience in the field of energy and environment modeling or in transportation policy and planning will be strongly appreciated.
Deadline for applications: 04/05/2010.