The Maelia project (Multi-Agent for Environmental Norms Impact Assessment) develops a digital platform for simulating the socio-environmental effects of Global Changes and the implementation of various norms of governance and management of water resources. To address the direct/indirect or expected/unexpected effects of these changes and norms, the platform couples a significant number of stylized dynamics categorized within three major domains: hydrology, agriculture and social. Maelia's contributions are focused on the modeling of low-water management, which is the most strategic issue regarding water resources in the Adour-Garonne basin.
The originality of the platform comes from a multiagent approach where a number of software agents simulate the many actors, material and cognitive resources dynamics playing a role in water management.
Maelia is a Java-based simulation platform whose HCI is provided by the Gama framework.
Several technical and conceptual challenges are investigated in Maelia. Managing the data and designing the processes at the heart of the simulation are the most important two.
Data manipulated in Maelia is gigantic and heterogeneous : GIS shapes, databases, PDF documents, spreadsheets, etc. Pre-processing all this data is therefore a mandatory step towards being able to use it. In maelia, every pre-processing routine has been made generic, toroughly documented, and re-usable.
Every change in the simulation is controlled by a process. Processes describe the resources at stake in an interaction between actors and resources, and the dynamics of this interaction. A specific methodology was designed on purpose.
A simulation of Maelia integrates many data sources and many simultaneous dynamics into a consistent whole whose evolution in time can be simulated.
The image below illustrates a simulation in the «Maelia basin» the watershed defined from the source of the Garonne river downstream to Toulouse, France, which was used for primary experimentations.
Two specific features make Maelia an original project.
The first one consists in a meticulous modeling of the evolution of the agricultural landscape. Based on detailed data from INRA Toulouse (The French National Institute for Agricultural Research), Maelia has developed a model to predict the yearly evolution of the agricultural patches and the culture types.
The evolution of culture types greedy in water (like corn or soya for instance) has a significant impact on low-water management.
Animation illustrating the evolution of the agricultural landscape in a small watershed on the outskirts of Toulouse. (drag mouse over the thumbnails)
The water withdrawal regulations play as significant a role as the choice of the culture. Maelia models the different norms that could be introduced and allow decision makers to test them beforehand.
The image opposite shows the different zones within the «Maelia basin» where restrictions may be applied during the low-water season.
The following video illutrates a simulation with a 3d rendering providing a better insight on the several data sources and dynamics represented in the multiagent simulation. From the center outward (eg. from the right ot the frame leftward) : air temperature, water flow debit, water withdrawal restriction level, culture type rotation, crop growth, farmer's activity and pluviometry.