A Joint Space-Time Probabilistic Model for Agricultural Droughts, Hydrological Droughts and Fire Weather in France

Abstract. Agricultural droughts, hydrological droughts and wildfires have significant environmental and socioeconomic consequences. These hazards are physically linked because they share a number of forcings, and their space-time properties are important as impacts result from their spatial extent and duration, in addition to their intensity. This paper introduces a probabilistic model adapted to the description of multiple spatial hazards, based on the combination of simple ingredients: regressions to describe dependencies between hazards, principal component analysis to describe spatial dependence, and simple covariance functions to describe time dependence and residual spatial dependence. This results in a modular framework that decomposes a complex model into several simpler models. This model is then used to analyze the observed Soil Wetness Index, Fire Weather Index and river flows in France over the last six decades, and in particular to estimate the probability of occurrence of the remarkable 2022 summer event. Locally, the 2022 summer was extreme in terms of agricultural drought over a large part of the country, but was rather moderate in terms of hydrological drought and fire weather. However, the magnitude, spatial extent and duration of the event become extreme nearly everywhere when the three hazards are considered together. The underlying trends affecting all three hazards have more than doubled the probability of the event during the historical period, and future projections suggest that it might become common by the end of the century with global warming.