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International audience; The predominantly agricultural Mekong Delta region will be profoundly affected by the effects of climate change, such as rising temperatures, sea level rise, and salinization. But recent studies show that other factors, such as sand mining and groundwater exploitation, will also largely contribute to future pressures, particularly through land subsidence. Alongside the fight against climate change, this makes it necessary to design strategies and policies for subsidence mitigation, not only at the individual level (mainly farmers), but also at the institutional level (province and region). Indeed, in the Vietnamese Mekong Delta (VMD), local provinces play a crucial role in the choice and implementation of strategies for the exploitation of natural resources, such as water or sand. However, the VMD is also a complex system in which the decisions of one province can have indirect effects on the other 12 provinces, especially because some provinces share common agro-ecological regions and aquifer areas. This chapter aims to explore, through simulation of an integrated model, the economic impact on farmers of the adaptation strategies chosen by the provinces under a number of climatic and economic scenarios. It thus builds on the adaptation options evaluated in Part 3 of the report. In particular, one objective is to understand which conditions of inter-province coordination on groundwater exploitation in common agro-ecological areas could improve the economic situation of farmers. To this end, the LUCAS model (an agent-based model for land-use change adaptation strategies in the context of climate change) [ Truong et al., 2021 ] was extended to take groundwater use by farmers into account, as well as the subsidence dynamics and macroeconomic trends from the GEMMES model. In the updated model, called LUCAS-GEMMES, subsidence-related adaptation strategies chosen at the provincial level and their interactions with individual decisions were also introduced. The simulation is performed with 4 experiments including (i) No provincial adaptation strategies and ignorance of subsidence dynamics; (ii) No adaptation strategies while subsidence impacts the benefit of land-use production; (iii) Individual adaptation strategies combined with the impact of subsidence; (iv) Province and individual adaptation combined with the impact of subsidence.The results show that decisions in early response to low-level subsidence bring many positive results in resource management, such as significantly reducing water use in the dry season, and reducing the vulnerability area from subsidence and climate change. The results also show a decrease in incomes in case of adaptation. Therefore, it is necessary to have investment solutions (technical support in shrimp farming, studying for new upland crops in the dry season) for new land-use types that could compensate for the economic benefits lost when applying policies that restrict people in the use of resources.; La région du delta du Mékong, essentiellement agricole, sera profondément touchée par les effets du changement climatique, tels que la hausse des températures, l’élévation du niveau de la mer et la salinisation. Mais des études récentes montrent que d’autres facteurs, comme l’extraction de sable et l’exploitation des eaux souterraines, contribueront également fortement aux pressions futures, notamment par la subsidence. Au-delà de la lutte contre le changement climatique, il est donc nécessaire de concevoir des stratégies et des politiques d’atténuation de la subsidence, non seulement au niveau individuel (principalement les agriculteurs), mais aussi au niveau institutionnel (province et région). En effet, dans le delta du Mékong vietnamien (DMV), les provinces locales jouent un rôle crucial dans le choix et la mise en œuvre des stratégies d’exploitation des ressources naturelles, comme l’eau ou le sable. Cependant, le DMV est aussi un système complexe dans lequel les décisions d’une province peuvent avoir des effets indirects sur les 12 autres provinces, notamment parce que certaines provinces partagent des régions agro-écologiques et des zones aquifères communes. Ce chapitre vise à explorer, par la simulation d’un modèle intégré, l’impact économique sur les agriculteurs des stratégies d’adaptation choisies par les provinces dans un certain nombre de scénarios climatiques et économiques. Il s’appuie donc sur les options d’adaptation évaluées dans la partie 3 du rapport. En particulier, un objectif est de comprendre dans quelles conditions de coordination entre les provinces sur l’exploitation des eaux souterraines, dans des zones agro-écologiques communes, la situation économique des agriculteurs peut s’améliorer. À cette fin, le modèle LUCAS (un modèle “basé agents” pour les stratégies d’adaptation au changement d’utilisation des terres dans le contexte du changement climatique) [ Truong et al., 2021 ] a été étendu pour prendre en compte l’utilisation des eaux souterraines par les agriculteurs, ainsi que la dynamique de subsidence et les tendances macroéconomiques du modèle GEMMES. Dans le modèle mis à jour, appelé LUCAS-GEMMES, les stratégies d’adaptation liées à la subsidence choisies au niveau provincial et leurs interactions avec les décisions individuelles ont également été introduites. La simulation est réalisée à l’aide de quatre expériences : (i) aucune stratégie d’adaptation provinciale et ignorance de la dynamique de la subsidence ; (ii) aucune stratégie d’adaptation alors que la subsidence a un impact sur le bénéfice de la production de l’utilisation des terres ; (iii) stratégies d’adaptation individuelles combinées à l’impact de la subsidence ; (iv) adaptation provinciale et individuelle combinée à l’impact de la subsidence. Les résultats montrent que les décisions prises en réponse précoce à un affaissement de faible niveau apportent de nombreux résultats positifs dans la gestion des ressources, tels que la réduction significative de l’utilisation de l’eau pendant la saison sèche, puis la réduction de la zone de vulnérabilité à la subsidence et au changement climatique. Les résultats montrent également une diminution des revenus en cas d’adaptation. Par conséquent, il est nécessaire d’avoir des solutions d’investissement (soutien technique dans l’élevage de crevettes, étude de nouvelles cultures de montagne en saison sèche) pour de nouveaux types d’utilisation des terres qui compenseraient les avantages économiques perdus lors de l’application de politiques qui limitent les personnes dans l’utilisation des ressources.

International audience

International audience; GAMA is a modeling and simulation platform for creating simulations following a multi-agent approach. COMOKIT is a modeling kit written by GAMA for the purpose of analyzing and comparing the policies against the spread of the Covid 19 pandemic at the scale of a city. As a member of the COMOKIT project, with the mission of researching and developing to improve the user interaction and user interface on both GAMA and COMOKIT, we propose to develop a necessary feature for GAMA. That’s dashboard feature, a good means of communicating and analyzing information for the most fields today. Currently, GAMA platform provides users display chart types to support the analysis and visualization of data in the simulation, some of which have not yet available to put on a dashboard, for example: gauge type, metric type, data table type. However, the layout and the way to interact with the chart are limited, the output of simulation is not really user-friendly. This research will focus on creating a new syntax (GAML) in GAMA to use for displaying a dashboard in simulation. The generated syntax should be really easy to use, easy to understand and easy to edit. The dashboard is created allow users to arrange the charts depending on the research purpose. With the creation of a dashboard feature, it can be applied to specific research models such as COMOKIT, helping modelers to synthesize analytical data on the dashboard. From which to evaluate the results and effectivenesss of the research model correctly.

International audience; In recent years, the combined effects of fluctuations in the benefit of agricultural and seafood production, management policies and environmental changes (increase of saltwater intrusion due to subsidence and sea level rise, increase of the length of drought periods because of the elevation of temperatures and the decrease of freshwater availability) have seriously affected the agricultural production of the coastal provinces in the Mekong Delta. Adaptation of farmers take many forms, including deep changes in their agricultural practices and land-use in order to maintain their income. However, the somewhat uncontrolled conversion of farming systems to follow market demand and get immediate profits will in some cases negatively impact the environment (degradation of soils, increase of salinization) and locally disrupt the long-term land-use plans established by provinces, normally designed to be sustainable at the global scale. In this work, we focus on land-use decision in the Mekong Delta. This region is planned to be a sustainable land-use types, but farmers tend to shift from rice to shrimp farming systems due to economic reasons. These decisions endanger the planned sustainable development of the area and the effects of infrastructures built to reach the plan. It is thus necessary to study and forecast this conversion to support the land-use planning and recommend the best suitable strategy to farmers. However, this forecasting work is currently lacking tools. It is mainly based on the human-made land inventory carried out every 5 years, which is obviously made under times and human resources limitations. This work aims to apply an Agent-based model to support managers' decision-making and to provide a picture of the future to encourage people to choose land-use types. The model is designed by agent-based approach where farmers are represented as the cell from the land-use map and the description of their states and behaviors. The simulation will let them interact and from these interactions, the dynamics of the system is expected to emerge. Decision-making process is based on the multicriteria analysis in which farmers will thus have to make their decisions given environmental, climate and socio-economic changes. The input data for verification and calibration of the model have been collected from the existed land-use map in 2015 and interpreted from Sentinel 2 satellite images in 2020 for the land-use. The climate change scenarios are forecasting to 2030. The results of the experiments showed evolutions of land-use in 2030 with climate change scenarios to analyze farming risks when the environment (including temperature, rainfall, water volume) and prices change in a harsher direction.

International audience; Since its emergence in China late 2019, the COVID-19 pandemic has spread rapidly around the world. Faced with this unknown disease, public health authorities were forced to experiment, in a short period of time, with various combinations of interventions at different scales. The scientific community has quickly emerged as a centerpiece to resolve the various puzzles the virus was the origin of, including how to flatten the curve of infection, limit the spread of the pandemic, create and dispatch the vaccines, and what could be the treatments. One of the main expectations from policy makers was to be able to help them build an appropriate response and forecast the consequences: this has put lights upon epidemiological models like never before. To meet this demand, we have developed an agent-based modeling framework called COVID-19 Modeling Kit (COMOKIT), designed to be generic, scalable and thus portable in a variety of social and geographical contexts. COMOKIT combines models of person-to-person and environmental transmission, a model of individual epidemiological status evolution, an agenda-based 1-h time step model of human mobility, and an intervention model. It is designed to be modular and flexible enough to allow modelers and users to represent different strategies and study their impacts in multiple social, epidemiological or economic scenarios. Since its first version (COMOKIT 1.0 - presented in (Gaudou et al., 2020)), COMOKIT has deeply evolved, through different related projects such as the ANRS COMOKIT project, COMOKIT Camps on the transmission of covid in refugee camps, COMOKIT Azur on the impact of morpho-functional characteristics of cities or neighborhoods on the spread of the disease, COMOKIT Albatross on a large-scale application of COMOKIT in the Netherlands using data for the construction of individuals’ agendas: enrichment of the population generation process, better consideration of the link between the simulated territory and the outside area, accounting of variants and new types of interventions (e.g. vaccination), dashboard to better visualize data, multilevel modeling, etc. In this presentation, we propose to go back over COMOKIT, its evolutions, but also to look at the impact of COMOKIT on the development of the GAMA platform. Indeed, all the efforts put in COMOKIT have greatly shaped ideas for the future development of GAMA, mostly questioning the link between the platform, data and decision-making process.

International audience; According to recent studies, Vietnam is one of the twenty countries most affected by natural disasters in the world, and particularly by floods either on the low elevation coastal zones (risk of submersion) or along the Red River and the Mekong River (risk of flooding). In this context, dams are both means of mitigation but also threats given the possible failures and ruptures. The authorities must, therefore, prepare warning systems and evacuation plans for the downstream population to avoid loss of life. Agent-based models are now the approach of choice to support such preparedness by considering the system as a whole and integrating dynamics of different natures: hydrology, population behavior, evacuation, crisis management, etc. To design such a decision-support tool, modelers generally need to couple different formalisms, such as diffusion equations when considering the hydrodynamic part, and agent-based modeling when considering inhabitants’ behaviors. This is the goal of the ESCAPE project, which uses agent-based simulations to explore evacuation strategies and contribute to the development and evaluation of evacuation plans. In this study, to improve the ESCAPE framework, we propose to combine a hydraulic dam failure model with an agent-based evacuation model using the GAMA platform. We focus on the evacuation of a Hanoi city (Vietnam) district, threatened by flooding due to the failure of the Hoa Binh dam located more than 80 km upstream of the city. We demonstrate how to methodologically and operationally couple a hydrodynamic water diffusion model (implemented using the HEC-RAS software) and a multi-paradigm evacuation model (using the ESCAPE framework). Our goal is to extend and enrich this population evacuation model by coupling it with flood simulation.

International audience; Irrigation systems contribute worldwide to the provision of a wide range of services on which the survival and well-being of humanity depend. They are of primary importance in Vietnam where about 90% of the water used is for irrigation and aquaculture and where agriculture is the largest employer and a major contributor to the national GDP and to the income of the low-salary households. Nevertheless, irrigation systems have recently been subjected to several issues including increasing demand, pollution, under-investment, depletion of resources or environmental changes. Any mitigation measure against these issues needs to be sustainable with respect to the very diverse uses of the water, the changing conditions upstream and downstream, and the somewhat conflicting objectives carried out by land-use/agricultural planning on one hand and urbanization and society well-being on the other. This need of sustainability requires the design of innovative tools to tackle these issues. This work aims at exploring the usage of Agent-Based Modelling coupled with a tangible and interactive interface in order to enhance interactions between stakeholders and support the evaluation of various alternatives of the management of the Bac Hung Hai irrigation system.

Integrated modeling approaches (multi-simulation, multimodeling, etc.) have proven challenging in practice. The first challenge deals with the technical aspects of coupling different computational or mathematical components. The second challenge lies in the alignment of the semantics of these components so that their integration does make sense, which is particularly critical in pluridisciplinary models. A number of approaches have been proposed in the last 20 years but none of them is really suitable to our context . We propose in this thesis an alternate approach, called co-modeling, which borrows concepts and tools from agent-based modeling, agent-oriented software engineering and multimodel ecologies. Simply speaking, a co-model can be defined as a multi-agent system of models and datasets. Each model or dataset is represented by one or several agents interacting with one another within the context of a larger representation of their — potentially dynamic — environment. The proposed approach does not aim at providing a general solution to the two challenges above, but at providing a framework in which modelers can easily implement their solution or test different coupling solutions. The proposed approach is fully implemented within the GAMA agent-based modeling platform. Its advantages are shown in terms of flexibility, composability and reusability in a number of case studies. The first case study is the dynamic coupling of equation-based and agent-based models to obtain “switching” models dynamically. The second one is the design of a complex integrated model where three formalisms and four modeling approaches have been successfully coupled.; L'objectif initial de cette thèse est d'apporter une solution à ce problème en proposant, premièrement, une approche cognitive basée sur le paradigme appelé Belief-Desire-Intention (BDI) pour représenter les processus de prise de décision des acteurs humains, et deuxièmement, une validation de cette approche dans le contexte d'un modèle complet de changement d'usage des sols dans lequel la plupart des facteurs cités ci-dessus sont également simulés. Le résultat de ce travail est une approche générique qui a été validée sur un modèle intégrant le changement d'usage des sols d'une région située dans le Delta du Mékong au Vietnam. Nos contributions principales sont les suivantes : Intégration d'une architecture BDI au sein d'une plateforme de modélisation à base d'agents (GAMA) ; Conception d'un cadre générique baptisé " Multi-Agent Based Land-Use Change " (MAB-LUC) permettant de modéliser et de simuler les changements d'usage des sols en prenant en compte les décisions des agriculteurs ; Proposition d'une solution permettant d'intégrer et d'évaluer les facteurs socio-économiques et environnementaux dans le cadre de la planification agraire et d'intégrer MAB-LUC dans le processus existant proposé par la FAO. Ce travail, au-delà du cas d'étude concernant le Delta du Mékong, a enfin été conçu de façon générique afin que la méthodologie utilisée puisse être généralisée à la modélisation de systèmes socio-écologiques où les facteurs humains doivent être représentés avec précision.

International audience; The ecology modeling generally opposes two class of models, equations based models and multi-agents based models. Mathematical models allow predicting the long-term dynamics of the studied systems. However, the variability between individuals is difficult to represent, what makes these more suitable models for large and homogeneous populations. Multi-agent models allow representing the attributes and behavior of each individual and therefore provide a greater level of detail. In return, these systems are more difficult to analyze. These approaches have often been compared, but rarely used simultaneously. We propose a hybrid approach to couple equations models and agent-based models, as well as its implementation on the modeling platform Gama [7]. We focus on the representation of a classical theoretical epidemiological model (SIR model) and we illustrate the construction of a class of models based on it.

The ecology modeling generally opposes two class of models, equations based models and multi-agents based models. Mathematical models allow predicting the long-term dynamics of the studied systems. However, the variability between individuals is difficult to represent, what makes these more suitable models for large and homogeneous populations. Multi-agent models allow representing the attributes and behavior of each individual and therefore provide a greater level of detail. In return, these systems are more difficult to analyze. These approaches have often been compared, but rarely used simultaneously. We propose a hybrid approach to couple equations models and agent-based models, as well as its implementation on the modeling platform Gama [7]. We focus on the representation of a classical theoretical epidemiological model (SIR model) and we illustrate the construction of a class of models based on it.