Rainfall intensity–duration thresholds for bedload transport initiation in small Alpine watersheds

Abstract

Although channel discharge represents one of the primary controls of bedload transport rates in mountain streams, it is rarely measured in small, steep catchments. Thus, it is often impossible to use it as a predictor of hazardous bedload events. In this study, the characteristics of rainfall events leading to bedload transport were investigated in five small Alpine catchments located in different geographical and morphological regions of Switzerland, Italy and France. Using rainfall data at high temporal resolution, a total of 370 rainfall events were identified that led to abundant sediment transport in the different catchments, and corresponding threshold lines were defined using a power law in intensity–duration space. Even though considerable differences in the distribution of the rainfall data were identified between catchments located in various regions, the determined threshold lines show rather similar characteristics. <br><br> Such threshold lines indicate critical conditions for bedload transport initiation, but rainfall events that do not cause transport activity (so called no-bedload events) can still plot above them. With 0.67 overall in the Erlenbach (Swiss Prealps) and 0.90 for long-duration, low-intensity rainfall, the false alarm rate is considerable. However, for short-duration, high-intensity events, it is substantially smaller (0.33) and comparable to values determined in previous studies on the triggering of Alpine debris flows. Our results support the applicability of a traditional, generalized threshold for prediction or warning purposes during high-intensity rainfall. Such (often convective) rainfall events are unfortunately (i) difficult to measure, even by dense rain gauge networks, and (ii) difficult to accurately predict, both due to their small spatial and temporal scales. Still, for the protection of human life (e.g. along transportation infrastructure such as roads and railway) automated alerts based on power law threshold lines may be useful.