Understanding meteorological and physio-geographical controls of variability of flood event classes in China

Abstract

Abstract. Classification is beneficial for understanding flood variabilities and their formation mechanisms from massive flood event samples for both flood scientific research and management purposes. Our study investigates spatial and temporal variabilities of 1446 unregulated flood events in 68 headstream catchments in China at class scale using hierarchical and partitional clustering methods. Control mechanisms of meteorological and physio-geographical factors (e.g., meteorology, land cover and catchment attributes) are explored for individual flood event classes using constrained rank analysis and Monte Carlo permutation test. Results show that we identify five robust flood event classes, i.e., moderately, highly, and slightly fast floods, as well as moderately and highly slow floods, which accounts for 24.0 %, 21.2 %, 25.9 %, 13.5 % and 15.4 % of total events, respectively. All the classes are evenly distributed in the whole period, but the spatial distributions are quite distinct. The fast flood classes are mainly in the southern China, and the slow flood classes are mainly in the northern China and the transition region between southern and northern China. The meteorological category plays a dominant role in flood event variabilities, followed by catchment attributes and land covers. Precipitation factors, such as volume and intensity, and aridity index are the significant control factors. Our study provides insights into flood event variabilities and aids in flood prediction and control.