Résumé
In the context of climate change and growing urbanization, farms are expected to face more frequent extreme events (e.g. heat peaks, droughts, frost, hail or floods). Floods being the natural hazard that generates the most damage in the world, we focus our research on the impact of floods on farms and their adaptation to climate change. Flood damage on farms is the result of complex phenomena involving biophysical processes on the one hand, and farmers' decisions on rehabilitation and adaptation on the other. Some impacts are directly visible; others may be delayed and persist over time (Bremond et al, 2013). When they persist over time, they may impact the development trajectory of farms.
For the observation of impacts, there are in fact two challenges: to identify the diversity of impacts and their temporality of occurrence. Field surveys following flood events often focus on short-term damage and on impacts resulting from extreme events, leaving long-term damage and minor events aside. In this paper, we aim to propose a methodology that we are currently implementing to jointly and recursively improve the observation and modelling of flood impacts on agricultural systems. In particular, we wish to define more precisely the diversity of flood impacts and long-term damage on farms by taking into account the development trajectory of farms. To this end, we combine two complementary approaches: observation and modelling.
Our work is implemented in the framework of the system of observations of the impacts of floods (so-ii, so-ii.org), in the Greater Montpellier area, coordinated by our team. Based on our experience, we have developed diverse methods for both short-term and long-term monitoring such as: surveys, participative workshops, drone pictures, predictive models.
To cover on field-observations, quantitative and qualitative surveys have been carried out over the years on the so-ii territory. Interviews took place both after a flood, to gather quantitative data, and several years after a flood (Bremond et al, 2020), to collect quantitative and qualitative data. In parallel, we are exploring the use of drones to gather pictures of plots from post-flood to several years later in order to understand mechanisms behind the impacts of floods on soil, plant material and adaptations. To reinforce long-term monitoring, we have set up a network of impact observers, on the so-ii territory, with whom we agreed to work over the long-term (about fifteen years).
On the other hand, we are working on the use of predictive models to estimate flood damage to farms. For now, 3 models have been developed: floodam.agri (Bremond et al, 2022), R-EVA (Bremond et al, 2012) and COOPER (Nortes Martinez et al, 2021). Each of these models have different application levels (respectively plot, farm and cooperative system) and time-scales which helps for the observation of farm trajectories as a whole.
In conclusion, we will discuss the perspectives and limitations of this approach. We will open up on the perspectives to share our methodology so it can be adapted to other territories by stakeholders who are interested in setting up a similar system of observation.