Identification of catchments with similar hydro-meteorological conditions during rainfall-runoff events: An event-based clustering approach for 378 catchments in the contiguous United States

The rainfall-runoff process at the catchment scale is governed by a complex interplay of physical and climatic driving mechanisms that vary in space and time. Although this variability makes it challenging to generalize catchment hydrological processes, classifying catchments in terms of their similarity can help identify spatial patterns with implications for e.g., the prediction of hydrological processes in ungauged locations. Previous studies identified spatial patterns of catchments with similar driving mechanisms of the rainfall-runoff process at the event scale by grouping catchments according to e.g., event runoff coefficients, event timescales (ratio of total event runoff to peak event runoff), or correlation coefficients between runoff characteristics and hydro-meteorological variables. However, the variability of rainfall-runoff events in a catchment over time has rarely been taken into account in previous catchment classification schemes. Here, we applied an event-based two-stage clustering approach to 378 essentially snow-free catchments with diverse physical and climate attributes in the contiguous United States. First, we clustered runoff events based on selected event runoff characteristics in each catchment into three clusters containing different event runoff shapes of short, medium, and long event timescales (catchment scale). Then, we clustered the catchments based solely on their hydro-meteorological event conditions corresponding to the three event runoff clusters and evaluated the identified catchment groups in terms of their physical and climate attributes (continental scale). As a result, we derived five groups comprising catchments with similar hydro-meteorological event conditions for the three event runoff shapes, revealing a distinct spatial pattern: In catchments dominated by a humid climate with low rainfall seasonality (number of catchments n=126), mean event rainfall intensities were primarily decisive for the clustering of event runoff into different shapes. In catchments of similar climate but larger forest cover, both mean event rainfall intensities and total event rainfall sums influenced the event clustering (n=116). In very humid regions (aridity index < 0.5) showing high rainfall seasonality (n=28), the total event rainfall sum was the only factor determining the event timescale. Furthermore, in arid lowland catchments with high rainfall seasonality (n=57), the event timescale increased with increasing antecedent soil moisture, similar to the group of arid catchments with comparably lower rainfall seasonality (n=51). Thus, we assume that in arid catchments, during dry conditions, rainfall quickly became runoff via e.g., overland flow, while during wetter conditions, slower catchment flow paths were activated (subsurface flow), leading to larger event timescales. Conversely, in humid catchments, soil water storage varied less, so rainfall characteristics themselves primarily determined the shape of runoff events. Our study demonstrates that using an event-based clustering approach results in meaningful spatial catchment groups, complementing catchment classification schemes based on long-term hydrological signatures. By focusing on the temporal variability of event runoff shapes within a catchment, regions comprising catchments with similar hydro-meteorological event conditions decisive for this variability can be identified.