Regional process-based analysis of trends in flood peaks and volumes using hourly data

Most studies on flood trends rely on daily discharge data at the station scale, limiting their ability to disentangle contrasting trends in different flood-generation mechanisms. This is particularly true for capturing short-duration processes such as flash floods. Here, we propose a process-based regional framework to investigate trends across different flood types using hourly data. We analyze 829 small to medium-sized catchments (<500 km 2 ) across France using hourly discharge, radar rainfall, and reanalysis-based soil moisture data. Flood events are extracted using a peaks-over-threshold approach and classified into four categories based on response time (flash vs. slow) and antecedent soil moisture conditions (saturated vs. non-saturated). Catchments are grouped into four homogeneous hydro-climatic regions, and a spatio-temporal declustering procedure is applied to account for spatial and temporal dependence between concurrent events. Trends in flood peaks and direct runoff volumes are then assessed using regional quantile regression. Results reveal strong contrasts between regions and flood types. Only a few trends were detected for flood peaks, whereas flood volumes exhibit more frequent significant increasing trends. The strongest increases are found for flash flood volumes in mountainous and Mediterranean regions. For slow-onset floods, significant positive volume trends are observed in basins located in temperate regions, in line with increases in both rainfall totals and duration. Overall, flood volumes show a systematically higher sensitivity to change than peak flows. These findings demonstrate that flood trend detection critically depends on temporal resolution, flood type, and regional context, and that volume-based metrics provide complementary and often stronger signals than peak-based indicators for assessing evolving flood hazards.